Forest landscape mosaics: Disturbance, restoration, and management at times of global change

Treesearch

Kalev Jogiste; Bengt Gunnar Jonsson; Timo Kuuluvainen; Sylvie Gauthier; W. Keith Moser

2015-01-01

Potential effects of hypothesized anthropogenic climate change are raising concerns about the sustainability of development in terms of both people and the rest of the environment. Land use change at the global scale presents many challenges for the research community. Past land use has a definite effect on future ecosystems, but it is challenging to predict future...

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M. P.; Arvidson, R. E.; Bell, J. F., III; Christensen, P. R.; Crisp, J. A.; Ehlmann, B. L.; Fergason, R. L.; Grant, J. A.; Haldemann, A. F. C.; Parker, T. J.;

PREDICTING THE RELATIVE IMPACTS OF URBAN DEVELOPMENT POLICIES AND ON-ROAD VEHICLE TECHNOLOGIES ON AIR QUALITY IN THE UNITED STATES: MODELING AND ANALYSIS OF A CASE STUDY IN AUSTIN, TEXAS

EPA Science Inventory

Urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition that influence future predictions of air quality. This study examines the impacts of alter...

Emergency post-fire rehabilitation treatment effects on burned area ecology and long-term restoration

Treesearch

Peter R. Robichaud; Sarah A. Lewis; Robert E. Brown; Louise E. Ashmun

2009-01-01

The predicted continuation of strong drying and warming trends in the southwestern United States underlies the associated prediction of increased frequency, area, and severity of wildfires in the coming years. As a result, the management of wildfires and fire effects on public lands will continue to be a major land management priority for the foreseeable future....

Simulation of future land use change and climate change impacts on hydrological processes in a tropical catchment

NASA Astrophysics Data System (ADS)

Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.

2017-12-01

Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment

Effects of future urban and biofuel crop expansions on the riverine export of phosphorus to the Laurentian Great Lakes

USGS Publications Warehouse

LaBeau, Meredith B.; Robertson, Dale M.; Mayer, Alex S.; Pijanowski, Bryan C.; Saad, David A.

2013-01-01

Increased phosphorus (P) loadings threaten the health of the world’s largest freshwater resource, the Laurentian Great Lakes (GL). To understand the linkages between land use and P delivery, we coupled two spatially explicit models, the landscape-scale SPARROW P fate and transport watershed model and the Land Transformation Model (LTM) land use change model, to predict future P export from nonpoint and point sources caused by changes in land use. According to LTM predictions over the period 2010–2040, the GL region of the U.S. may experience a doubling of urbanized areas and agricultural areas may increase by 10%, due to biofuel feedstock cultivation. These land use changes are predicted to increase P loadings from the U.S. side of the GL basin by 3.5–9.5%, depending on the Lake watershed and development scenario. The exception is Lake Ontario, where loading is predicted to decrease by 1.8% for one scenario, due to population losses in the drainage area. Overall, urban expansion is estimated to increase P loadings by 3.4%. Agricultural expansion associated with predicted biofuel feedstock cultivation is predicted to increase P loadings by an additional 2.4%. Watersheds that export P most efficiently and thus are the most vulnerable to increases in P sources tend to be found along southern Lake Ontario, southeastern Lake Erie, western Lake Michigan, and southwestern Lake Superior where watershed areas are concentrated along the coastline with shorter flow paths. In contrast, watersheds with high soil permeabilities, fractions of land underlain by tile drains, and long distances to the GL are less vulnerable.

Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

PubMed

Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

2017-10-17

Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.

Current and future land use around a nationwide protected area network

USGS Publications Warehouse

Hamilton, Christopher M.; Martinuzzi, Sebastian; Plantinga, Andrew J.; Radeloff, Volker C.; Lewis, David J.; Thogmartin, Wayne E.; Heglund, Patricia J.; Pidgeon, Anna M.

2013-01-01

Land-use change around protected areas can reduce their effective size and limit their ability to conserve biodiversity because land-use change alters ecological processes and the ability of organisms to move freely among protected areas. The goal of our analysis was to inform conservation planning efforts for a nationwide network of protected lands by predicting future land use change. We evaluated the relative effect of three economic policy scenarios on land use surrounding the U.S. Fish and Wildlife Service's National Wildlife Refuges. We predicted changes for three land-use classes (forest/range, crop/pasture, and urban) by 2051. Our results showed an increase in forest/range lands (by 1.9% to 4.7% depending on the scenario), a decrease in crop/pasture between 15.2% and 23.1%, and a substantial increase in urban land use between 28.5% and 57.0%. The magnitude of land-use change differed strongly among different USFWS administrative regions, with the most change in the Upper Midwestern US (approximately 30%), and the Southeastern and Northeastern US (25%), and the rest of the U.S. between 15 and 20%. Among our scenarios, changes in land use were similar, with the exception of our “restricted-urban-growth” scenario, which resulted in noticeably different rates of change. This demonstrates that it will likely be difficult to influence land-use change patterns with national policies and that understanding regional land-use dynamics is critical for effective management and planning of protected lands throughout the U.S.

Land cover changes associated with recent energy development in the Williston Basin; Northern Great Plains, USA

USGS Publications Warehouse

Preston, Todd M.; Kim, Kevin

2016-01-01

The Williston Basin in the Northern Great Plains has experienced rapid energy development since 2000. To evaluate the land cover changes resulting from recent (2000 – 2015) development, the area and previous land cover of all well pads (pads) constructed during this time was determined, the amount of disturbed and reclaimed land adjacent to pads was estimated, land cover changes were analyzed over time for three different well types, and the effects from future development were predicted. The previous land cover of the 12,990 ha converted to pads was predominately agricultural (49.5%) or prairie (47.4%) with lesser amounts of developed (2.3%), aquatic (0.5%), and forest (0.4%). Additionally, 12,121 ha have likely been disturbed and reclaimed. The area required per gas well remained constant through time while the land required per oil well increased initially and then decreased as development first shifted from conventional to unconventional drilling and then to multi-bore pads. For non-oil-and- gas wells (i.e. stratigraphic test wells, water wells, injection wells, etc.), the area per well increased through time likely due to increased produced water disposal requirements. Future land cover change is expected to be 2.7 times greater than recent development with much of the development occurring in five counties in the core Bakken development area. Direct land cover change and disturbance from recent and expected development are predicted to affect 0.4% of the landscape across the basin; however, in the core Bakken development area, 2.3% of the landscape will be affected including 2.1% of the remaining grassland. Although future development will result in significant land cover change, evolving industry practices and proactive siting decisions, such as development along energy corridors and placing pads in areas previously altered by human activity, have the potential to reduce the ecological effects of future energy development in the Williston Basin.

An exploratory investigation of the STOL landing maneuver

NASA Technical Reports Server (NTRS)

Whyte, P. H.

1979-01-01

The parameters influencing the STOL landing are identified and their effect on the ease and quality of the flare maneuver is discussed. Data from actual landings, supported by pilot commentary and pilot opinion rating, are analyzed. Hypotheses concerning the prediction of STOL handling qualities in the flare are proposed, and suggestions for future research are presented.

Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon

USGS Publications Warehouse

Coyan, Joshua; Zientek, Michael L.; Mihalasky, Mark J.

2017-01-01

Resource managers and agencies involved with planning for future federal land needs are required to complete an assessment of and forecast for future land use every ten years. Predicting mining activities on federal lands is difficult as current regulations do not require disclosure of exploration results. In these cases, historic mining claims may serve as a useful proxy for determining where mining-related activities may occur. We assess the utility of using a space–time cube (STC) and associated analyses to evaluate and characterize mining claim activities around the McDermitt Caldera in northern Nevada and southern Oregon. The most significant advantage of arranging the mining claim data into a STC is the ability to visualize and compare the data, which allows scientists to better understand patterns and results. Additional analyses of the STC (i.e., Trend, Emerging Hot Spot, Hot Spot, and Cluster and Outlier Analyses) provide extra insights into the data and may aid in predicting future mining claim activities.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Change in agricultural land use constrains adaptation of national wildlife refuges to climate change

USGS Publications Warehouse

Hamilton, Christopher M.; Thogmartin, Wayne E.; Radeloff, Volker C.; Plantinga, Andrew J.; Heglund, Patricia J.; Martinuzzi, Sebastian; Pidgeon, Anna M.

2015-01-01

Land-use change around protected areas limits their ability to conserve biodiversity by altering ecological processes such as natural hydrologic and disturbance regimes, facilitating species invasions, and interfering with dispersal of organisms. This paper informs USA National Wildlife Refuge System conservation planning by predicting future land-use change on lands within 25 km distance of 461 refuges in the USA using an econometric model. The model contained two differing policy scenarios, namely a ‘business-as-usual’ scenario and a ‘pro-agriculture’ scenario. Regardless of scenario, by 2051, forest cover and urban land use were predicted to increase around refuges, while the extent of range and pasture was predicted to decrease; cropland use decreased under the business-as-usual scenario, but increased under the pro-agriculture scenario. Increasing agricultural land value under the pro-agriculture scenario slowed an expected increase in forest around refuges, and doubled the rate of range and pasture loss. Intensity of land-use change on lands surrounding refuges differed by regions. Regional differences among scenarios revealed that an understanding of regional and local land-use dynamics and management options was an essential requirement to effectively manage these conserved lands. Such knowledge is particularly important given the predicted need to adapt to a changing global climate.

Integrating land use and climate change scenarios and models into assessment of forested watershed services in Southern Thailand.

PubMed

Trisurat, Yongyut; Eawpanich, Piyathip; Kalliola, Risto

2016-05-01

The Thadee watershed, covering 112km(2), is the main source of water for agriculture and household consumption in the Nakhon Srithammarat Province in Southern Thailand. As the natural forests upstream have been largely degraded and transformed to fruit tree and rubber plantations, problems with landslides and flooding have resulted. This research attempts to predict how further land-use/land-cover changes during 2009-2020 and conceivable changes in rainfall may influence the future levels of water yield and sediment load in the Thadee River. Three different land use scenarios (trend, development and conservation) were defined in collaboration with the local stakeholders, and three different rainfall scenarios (average rainfall, climate change and extreme wet) were determined on the basis of literature sources. Spatially explicit empirical modelling was employed to allocate future land demands and to assess the contributions of land use and rainfall changes, considering both their separate and combined effects. The results suggest that substantial land use changes may occur from a large expansion of rubber plantations in the upper sub-watersheds, especially under the development land use scenario. The reduction of the current annual rainfall by approximately 30% would decrease the predicted water yields by 38% from 2009. According to the extreme rainfall scenario (an increase of 36% with respect to current rainfall), an amplification of 50% of the current runoff could result. Sensitivity analyses showed that the predicted soil loss is more responsive to changes in rainfall than to the compared land use scenarios alone. However, very high sediment load and runoff levels were predicted on the basis of combined intensified land use and extreme rainfall scenarios. Three conservation activities-protection, reforestation and a mixed-cropping system-are proposed to maintain the functional watershed services of the Thadee watershed region. Copyright © 2016 Elsevier Inc. All rights reserved.

Yield of undamaged slash pine stands in South Florida

Treesearch

O. Gordon Langdon

1961-01-01

Predictions of future timber yields are necessary for formulating management plans and for comparing timber growing with alternative land uses. One useful tool for making these predictions is a set of yield tables.

Using changes in agricultural utility to quantify future climate-induced risk to conservation.

PubMed

Estes, Lyndon D; Paroz, Lydie-Line; Bradley, Bethany A; Green, Jonathan M H; Hole, David G; Holness, Stephen; Ziv, Guy; Oppenheimer, Michael G; Wilcove, David S

2014-04-01

Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning. © 2013 Society for Conservation Biology.

Landing Gear Noise Prediction and Analysis for Tube-and-Wing and Hybrid-Wing-Body Aircraft

NASA Technical Reports Server (NTRS)

Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

2016-01-01

Improvements and extensions to landing gear noise prediction methods are developed. New features include installation effects such as reflection from the aircraft, gear truck angle effect, local flow calculation at the landing gear locations, gear size effect, and directivity for various gear designs. These new features have not only significantly improved the accuracy and robustness of the prediction tools, but also have enabled applications to unconventional aircraft designs and installations. Systematic validations of the improved prediction capability are then presented, including parametric validations in functional trends as well as validations in absolute amplitudes, covering a wide variety of landing gear designs, sizes, and testing conditions. The new method is then applied to selected concept aircraft configurations in the portfolio of the NASA Environmentally Responsible Aviation Project envisioned for the timeframe of 2025. The landing gear noise levels are on the order of 2 to 4 dB higher than previously reported predictions due to increased fidelity in accounting for installation effects and gear design details. With the new method, it is now possible to reveal and assess the unique noise characteristics of landing gear systems for each type of aircraft. To address the inevitable uncertainties in predictions of landing gear noise models for future aircraft, an uncertainty analysis is given, using the method of Monte Carlo simulation. The standard deviation of the uncertainty in predicting the absolute level of landing gear noise is quantified and determined to be 1.4 EPNL dB.

Simulating soil organic carbon stock as affected by land cover change and climate change, Hyrcanian forests (northern Iran).

PubMed

Soleimani, Azam; Hosseini, Seyed Mohsen; Massah Bavani, Ali Reza; Jafari, Mostafa; Francaviglia, Rosa

2017-12-01

Soil organic carbon (SOC) contains a considerable portion of the world's terrestrial carbon stock, and is affected by changes in land cover and climate. SOC modeling is a useful approach to assess the impact of land use, land use change and climate change on carbon (C) sequestration. This study aimed to: (i) test the performance of RothC model using data measured from different land covers in Hyrcanian forests (northern Iran); and (ii) predict changes in SOC under different climate change scenarios that may occur in the future. The following land covers were considered: Quercus castaneifolia (QC), Acer velutinum (AV), Alnus subcordata (AS), Cupressus sempervirens (CS) plantations and a natural forest (NF). For assessment of future climate change projections the Fifth Assessment IPCC report was used. These projections were generated with nine Global Climate Models (GCMs), for two Representative Concentration Pathways (RCPs) leading to very low and high greenhouse gases concentration levels (RCP 2.6 and RCP 8.5 respectively), and for four 20year-periods up to 2099 (2030s, 2050s, 2070s and 2090s). Simulated values of SOC correlated well with measured data (R 2 =0.64 to 0.91) indicating a good efficiency of the RothC model. Our results showed an overall decrease in SOC stocks by 2099 under all land covers and climate change scenarios, but the extent of the decrease varied with the climate models, the emissions scenarios, time periods and land covers. Acer velutinum plantation was the most sensitive land cover to future climate change (range of decrease 8.34-21.83tCha -1 ). Results suggest that modeling techniques can be effectively applied for evaluating SOC stocks, allowing the identification of current patterns in the soil and the prediction of future conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model.

PubMed

Lin, Yu-Pin; Lin, Yun-Bin; Wang, Yen-Tan; Hong, Nien-Ming

2008-02-04

Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH) and land-use change with the Conversion of Land use and itsEffects (CLUE-s) model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF) model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990-2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001-2025). TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001-2025 and less interspersed from 2005-2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990-2025. The proposedapproach is an effective means of enhancing land-use monitoring and management ofurbanized watersheds.

Predicting future forestland area: a comparison of econometric approaches.

Treesearch

SoEun Ahn; Andrew J. Plantinga; Ralph J. Alig

2000-01-01

Predictions of future forestland area are an important component of forest policy analyses. In this article, we test the ability of econometric land use models to accurately forecast forest area. We construct a panel data set for Alabama consisting of county and time-series observation for the period 1964 to 1992. We estimate models using restricted data sets-namely,...

Size-Frequency Distributions of Rocks on Mars and Earth Analog Sites: Implications for Future Landed Missions

NASA Technical Reports Server (NTRS)

Golombeck, M.; Rapp, D.

1996-01-01

The size-frequency distribution of rocks and the Vicking landing sites and a variety of rocky locations on the Earth that formed from a number of geologic processes all have the general shape of simple exponential curves, which have been combined with remote sensing data and models on rock abundance to predict the frequency of boulders potentially hazardous to future Mars landers and rovers.

Local modelling of land consumption in Germany with RegioClust

NASA Astrophysics Data System (ADS)

Hagenauer, Julian; Helbich, Marco

2018-03-01

Germany is experiencing extensive land consumption. This necessitates local models to understand actual and future land consumption patterns. This research examined land consumption rates on a municipality level in Germany for the period 2000-10 and predicted rates for 2010-20. For this purpose, RegioClust, an algorithm that combines hierarchical clustering and regression analysis to identify regions with similar relationships between land consumption and its drivers, was developed. The performance of RegioClust was compared against geographically weighted regression (GWR). Distinct spatially varying relationships across regions emerged, whereas population density is suggested as the central driver. Although both RegioClust and GWR predicted an increase in land consumption rates for east Germany for 2010-20, only RegioClust forecasts a decline for west Germany. In conclusion, both models predict for 2010-20 a rate of land consumption that suggests that the policy objective of reducing land consumption to 30 ha per day in 2020 will not be achieved. Policymakers are advised to take action and revise existing planning strategies to counteract this development.

Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years.

PubMed

Ballantyne, A P; Alden, C B; Miller, J B; Tans, P P; White, J W C

2012-08-02

One of the greatest sources of uncertainty for future climate predictions is the response of the global carbon cycle to climate change. Although approximately one-half of total CO(2) emissions is at present taken up by combined land and ocean carbon reservoirs, models predict a decline in future carbon uptake by these reservoirs, resulting in a positive carbon-climate feedback. Several recent studies suggest that rates of carbon uptake by the land and ocean have remained constant or declined in recent decades. Other work, however, has called into question the reported decline. Here we use global-scale atmospheric CO(2) measurements, CO(2) emission inventories and their full range of uncertainties to calculate changes in global CO(2) sources and sinks during the past 50 years. Our mass balance analysis shows that net global carbon uptake has increased significantly by about 0.05 billion tonnes of carbon per year and that global carbon uptake doubled, from 2.4 ± 0.8 to 5.0 ± 0.9 billion tonnes per year, between 1960 and 2010. Therefore, it is very unlikely that both land and ocean carbon sinks have decreased on a global scale. Since 1959, approximately 350 billion tonnes of carbon have been emitted by humans to the atmosphere, of which about 55 per cent has moved into the land and oceans. Thus, identifying the mechanisms and locations responsible for increasing global carbon uptake remains a critical challenge in constraining the modern global carbon budget and predicting future carbon-climate interactions.

Predicted future forest- and farmland development in western Oregon with and without land use zoning in effect.

Treesearch

Jeffrey D. Kline

2005-01-01

Oregon’s Land Use Planning Program is often cited as an exemplary approach to protecting forest and farm lands from development. In November 2004, Oregon voters approved a ballot measure—Measure 37—to require the state to compensate landowners for any property value losses resulting from land use regulations, including those adopted under the program. Because...

Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

NASA Astrophysics Data System (ADS)

Bouchachi, B.; Zhong, Y.

2017-09-01

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

Impact of climatic and environmental changes on flood-duration-frequencies in the Fengle Rriver (YangTze Basin, China)

NASA Astrophysics Data System (ADS)

Salles, Christian; Chu, Yin; Tournoud, Marie-George; Ou, Mengli; Perrin, Jean-Louis; Cres, François-Noël; Ma, Youhua

2016-04-01

Future water management challenges such as flood risk are highly relevant to climate and land use changes. Climate change is expected to lead to an ongoing intensification of effects on changes in precipitation and evapotranspiration which could exacerbate flooding issues. Land use changes, modifications of agricultural practices and urbanization alter the apportionment of the different hydrological processes at the basin scale and could significantly affect the seasonality of streamflow. At the local scale, the consequences of climate and land use changes on flood occurrence and magnitude are a major issue for the economic development and management policy of basin area. This study apply a methodology for investigating the potential consequences of land use ,as well as precipitation and temperature changes on flood occurrence, duration and magnitude, accounting for uncertainties in scenario data and hydrological model parameters. The discharge time series predicted for the future were simulated from a calibrated and validated distributed hydrological model. The model was run from inputs which are -predicted rainfall time series based on scenarios of changes identified from a literature review, -future evapotranspiration rates assessed from temperature changes identified from a literature review -and scenarios of land-use changes The study area, the Fengle River basin (1500 km2), is located in the northeast part of Yangtze basin. The river is one of the main tributaries of the Chao Lake, the fifth largest natural lake of China. The lake catchment is 9130 km2 in area, including the city of Hefei and a large extent of agricultural and rural areas. Many changes are expected in land use and agricultural practices in the future, due to the touristic appeal of the Chao Lake shore and the growth of the city of Hefei. Climate changes are also expected in this region, with a high impact on rainfall regime. In the current period heavy storms and floods occur predominantly during summer. Using the above methodology the future dynamics of the Fengle River is characterized on discharge-duration-frequency curves. Results will be discussed with regards to the sensitivity of predicted flood occurrence, duration and magnitude by quantifying the impact of rainfall, temperature and land-use changes.

Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok, India

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Anirban; Mondal, Arun; Mukherjee, Sandip; Khatua, Dipam; Ghosh, Subhajit; Mitra, Debasish; Ghosh, Tuhin

2014-08-01

In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.

Airframe Noise Studies: Review and Future Direction

NASA Technical Reports Server (NTRS)

Rackl, Robert G.; Miller, Gregory; Guo, Yueping; Yamamoto, Kingo

2005-01-01

This report contains the following information: 1) a review of airframe noise research performed under NASA's Advanced Subsonic Transport (AST) program up to the year 2000, 2) a comparison of the year 1992 airframe noise predictions with those using a year 2000 baseline, 3) an assessment of various airframe noise reduction concepts as applied to the year 2000 baseline predictions, and 4) prioritized recommendations for future airframe noise reduction work. NASA's Aircraft Noise Prediction Program was the software used for all noise predictions and assessments. For future work, the recommendations for the immediate future focus on the development of design tools sensitive to airframe noise treatment effects and on improving the basic understanding of noise generation by the landing gear as well as on its reduction.

Application of genetic algorithm to land use optimization for non-point source pollution control based on CLUE-S and SWAT

NASA Astrophysics Data System (ADS)

Wang, Qingrui; Liu, Ruimin; Men, Cong; Guo, Lijia

2018-05-01

The genetic algorithm (GA) was combined with the Conversion of Land Use and its Effect at Small regional extent (CLUE-S) model to obtain an optimized land use pattern for controlling non-point source (NPS) pollution. The performance of the combination was evaluated. The effect of the optimized land use pattern on the NPS pollution control was estimated by the Soil and Water Assessment Tool (SWAT) model and an assistant map was drawn to support the land use plan for the future. The Xiangxi River watershed was selected as the study area. Two scenarios were used to simulate the land use change. Under the historical trend scenario (Markov chain prediction), the forest area decreased by 2035.06 ha, and was mainly converted into paddy and dryland area. In contrast, under the optimized scenario (genetic algorithm (GA) prediction), up to 3370 ha of dryland area was converted into forest area. Spatially, the conversion of paddy and dryland into forest occurred mainly in the northwest and southeast of the watershed, where the slope land occupied a large proportion. The organic and inorganic phosphorus loads decreased by 3.6% and 3.7%, respectively, in the optimized scenario compared to those in the historical trend scenario. GA showed a better performance in optimized land use prediction. A comparison of the land use patterns in 2010 under the real situation and in 2020 under the optimized situation showed that Shennongjia and Shuiyuesi should convert 1201.76 ha and 1115.33 ha of dryland into forest areas, respectively, which represented the greatest changes in all regions in the watershed. The results of this study indicated that GA and the CLUE-S model can be used to optimize the land use patterns in the future and that SWAT can be used to evaluate the effect of land use optimization on non-point source pollution control. These methods may provide support for land use plan of an area.

Landing Site Dispersion Analysis and Statistical Assessment for the Mars Phoenix Lander

NASA Technical Reports Server (NTRS)

Bonfiglio, Eugene P.; Adams, Douglas; Craig, Lynn; Spencer, David A.; Strauss, William; Seelos, Frank P.; Seelos, Kimberly D.; Arvidson, Ray; Heet, Tabatha

2008-01-01

The Mars Phoenix Lander launched on August 4, 2007 and successfully landed on Mars 10 months later on May 25, 2008. Landing ellipse predicts and hazard maps were key in selecting safe surface targets for Phoenix. Hazard maps were based on terrain slopes, geomorphology maps and automated rock counts of MRO's High Resolution Imaging Science Experiment (HiRISE) images. The expected landing dispersion which led to the selection of Phoenix's surface target is discussed as well as the actual landing dispersion predicts determined during operations in the weeks, days, and hours before landing. A statistical assessment of these dispersions is performed, comparing the actual landing-safety probabilities to criteria levied by the project. Also discussed are applications for this statistical analysis which were used by the Phoenix project. These include using the statistical analysis used to verify the effectiveness of a pre-planned maneuver menu and calculating the probability of future maneuvers.

Incorporating Land-Use Mapping Uncertainty in Remote Sensing Based Calibration of Land-Use Change Models

NASA Astrophysics Data System (ADS)

Cockx, K.; Van de Voorde, T.; Canters, F.; Poelmans, L.; Uljee, I.; Engelen, G.; de Jong, K.; Karssenberg, D.; van der Kwast, J.

2013-05-01

Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means of a particle filter data assimilation approach that incorporates uncertainty in land-use mapping and land-use model parameter assessment into the calibration process. This paper focuses on part of this work, more in particular the modelling of uncertainties associated with the impervious surface cover estimation and urban land-use classification adopted in the land-use mapping approach. Both stages are submitted to a Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The approach was applied on the central part of the Flanders region (Belgium), using a time-series of Landsat/SPOT-HRV data covering the years 1987, 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original classification, it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, incorporating uncertainty in the land-use change model calibration through particle filter data assimilation is proposed to address the uncertainty observed in the derived land-use maps and to reduce uncertainty in future land-use predictions.

Modelling of land use change in Indramayu District, West Java Province

NASA Astrophysics Data System (ADS)

Handayani, L. D. W.; Tejaningrum, M. A.; Damrah, F.

2017-01-01

Indramayu District into a strategic area for a stopover and overseas from East Java area because Indramayu District passed the north coast main lane, which is the first as the economic lifeblood of the Java Island. Indramayu District is part of mainstream economic Java pathways so that physical development of the area and population density as well as community activities grew by leaps and bounds. Growth acceleration raised the level of land use change. Land use change and population activities in coastal area would reduce the carrying capacity and impact on environmental quality. This research aim to analyse landuse change of years 2000 and 2011 in Indramayu District. Using this land use change map, we can predict the condition of landuse change of year 2022 in Indramayu District. Cellular Automata Markov (Markov CA) Method is used to create a spatial model of land use changes. The results of this study are predictive of land use in 2022 and the suitability with Spatial Plan (RTRW). A settlement increase predicted to continue in the future the designation of the land according to the spatial plan should be maintained.

Tradeoffs among carbon, biodiversity, and economic returns for future land-use scenarios in the conterminous United States

NASA Astrophysics Data System (ADS)

Pennington, D. N.; Nelson, E.; Polasky, S.; Plantinga, A.; Lewis, D.; Whithey, J.; Radeloff, V.; Lawler, J.; White, D.; Martinuzzi, S.; Helmers, D.; Lonsdorf, E.

2011-12-01

Land-use change significantly contributes to biodiversity loss, changes ecosystem processes, and causes ultimately the loss of ecosystem services. Planning for a sustainable future requires a thorough understanding of expected future land use at both the fine-spatial scale relevant for many ecological processes and at the larger regional levels relevant for large-scale policy making. We use an econometric model to predict business as usual land-use change across the continental US with 100-m resolution in 5-year time steps from 2001 to 2051. We then simulate the affect of various national-level tax, subsidy, and zoning policies on expected land-use change over this time frame. Further, we model the impact of projected land-use change under business as usual and the various policy scenarios on carbon sequestration and biodiversity conservation in the conterminous United States. Our results showed that overall, land use composition will remain fairly stable, but there are considerable regional changes. Differences among policy scenarios were relatively minor highlighting that the underlying economic drivers of land use patterns are strong, and even fairly drastic policies may not be able to change these.

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Past and predicted future changes in the land cover of the Upper Mississippi River floodplain, USA

USGS Publications Warehouse

De Jager, N. R.; Rohweder, J.J.; Nelson, J.C.

2013-01-01

This study provides one historical and two alternative future contexts for evaluating land cover modifications within the Upper Mississippi River (UMR) floodplain. Given previously documented changes in land use, river engineering, restoration efforts and hydro-climatic changes within the UMR basin and floodplain, we wanted to know which of these changes are the most important determinants of current and projected future floodplain land cover. We used Geographic Information System data covering approximately 37% of the UMR floodplain (3232 km2) for ca 1890 (pre-lock and dam) and three contemporary periods (1975, 1989 and 2000) across which river restoration actions have increased and hydro-climatic changes have occurred. We further developed two 50-year future scenarios from the spatially dependent land cover transitions that occurred from 1975 to 1989 (scenario A) and from 1989 to 2000 (scenario B) using Markov models.Land cover composition of the UMR did not change significantly from 1975 to 2000, indicating that current land cover continues to reflect historical modifications that support agricultural production and commercial navigation despite some floodplain restoration efforts and variation in river discharge. Projected future land cover composition based on scenario A was not significantly different from the land cover for 1975, 1989 or 2000 but was different from the land cover of scenario B, which was also different from all other periods. Scenario B forecasts transition of some forest and marsh habitat to open water by the year 2050 for some portions of the northern river and projects that some agricultural lands will transition to open water in the southern portion of the river. Future floodplain management and restoration planning efforts in the UMR should consider the potential consequences of continued shifts in hydro-climatic conditions that may occur as a result of climate change and the potential effects on floodplain land cover.

Land use planning and wildfire: development policies influence future probability of housing loss

USGS Publications Warehouse

Syphard, Alexandra D.; Massada, Avi Bar; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species

PubMed Central

Geary, Matthew; Fielding, Alan H.; McGowan, Philip J. K.; Marsden, Stuart J.

2015-01-01

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5–30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and ‘increased grazing’ (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the ‘reduced grazing’ scenario were nonlinear. ‘Scenario-led’ landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse. PMID:26569604

Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

PubMed

Alimi, Temitope O; Fuller, Douglas O; Qualls, Whitney A; Herrera, Socrates V; Arevalo-Herrera, Myriam; Quinones, Martha L; Lacerda, Marcus V G; Beier, John C

2015-08-20

Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

How will climate change pathways and mitigation options alter incidence of vector-borne diseases? A framework for leishmaniasis in South and Meso-America

PubMed Central

Masante, Dario; Golding, Nicholas; Pigott, David; Day, John C.; Ibañez-Bernal, Sergio; Kolb, Melanie; Jones, Laurence

2017-01-01

The enormous global burden of vector-borne diseases disproportionately affects poor people in tropical, developing countries. Changes in vector-borne disease impacts are often linked to human modification of ecosystems as well as climate change. For tropical ecosystems, the health impacts of future environmental and developmental policy depend on how vector-borne disease risks trade off against other ecosystem services across heterogeneous landscapes. By linking future socio-economic and climate change pathways to dynamic land use models, this study is amongst the first to analyse and project impacts of both land use and climate change on continental-scale patterns in vector-borne diseases. Models were developed for cutaneous and visceral leishmaniasis in the Americas—ecologically complex sand fly borne infections linked to tropical forests and diverse wild and domestic mammal hosts. Both diseases were hypothesised to increase with available interface habitat between forest and agricultural or domestic habitats and with mammal biodiversity. However, landscape edge metrics were not important as predictors of leishmaniasis. Models including mammal richness were similar in accuracy and predicted disease extent to models containing only climate and land use predictors. Overall, climatic factors explained 80% and land use factors only 20% of the variance in past disease patterns. Both diseases, but especially cutaneous leishmaniasis, were associated with low seasonality in temperature and precipitation. Since such seasonality increases under future climate change, particularly under strong climate forcing, both diseases were predicted to contract in geographical extent to 2050, with cutaneous leishmaniasis contracting by between 35% and 50%. Whilst visceral leishmaniasis contracted slightly more under strong than weak management for carbon, biodiversity and ecosystem services, future cutaneous leishmaniasis extent was relatively insensitive to future alternative socio-economic pathways. Models parameterised at narrower geographical scales may be more sensitive to land use pattern and project more substantial changes in disease extent under future alternative socio-economic pathways. PMID:29020041

How will climate change pathways and mitigation options alter incidence of vector-borne diseases? A framework for leishmaniasis in South and Meso-America.

PubMed

Purse, Bethan V; Masante, Dario; Golding, Nicholas; Pigott, David; Day, John C; Ibañez-Bernal, Sergio; Kolb, Melanie; Jones, Laurence

2017-01-01

The enormous global burden of vector-borne diseases disproportionately affects poor people in tropical, developing countries. Changes in vector-borne disease impacts are often linked to human modification of ecosystems as well as climate change. For tropical ecosystems, the health impacts of future environmental and developmental policy depend on how vector-borne disease risks trade off against other ecosystem services across heterogeneous landscapes. By linking future socio-economic and climate change pathways to dynamic land use models, this study is amongst the first to analyse and project impacts of both land use and climate change on continental-scale patterns in vector-borne diseases. Models were developed for cutaneous and visceral leishmaniasis in the Americas-ecologically complex sand fly borne infections linked to tropical forests and diverse wild and domestic mammal hosts. Both diseases were hypothesised to increase with available interface habitat between forest and agricultural or domestic habitats and with mammal biodiversity. However, landscape edge metrics were not important as predictors of leishmaniasis. Models including mammal richness were similar in accuracy and predicted disease extent to models containing only climate and land use predictors. Overall, climatic factors explained 80% and land use factors only 20% of the variance in past disease patterns. Both diseases, but especially cutaneous leishmaniasis, were associated with low seasonality in temperature and precipitation. Since such seasonality increases under future climate change, particularly under strong climate forcing, both diseases were predicted to contract in geographical extent to 2050, with cutaneous leishmaniasis contracting by between 35% and 50%. Whilst visceral leishmaniasis contracted slightly more under strong than weak management for carbon, biodiversity and ecosystem services, future cutaneous leishmaniasis extent was relatively insensitive to future alternative socio-economic pathways. Models parameterised at narrower geographical scales may be more sensitive to land use pattern and project more substantial changes in disease extent under future alternative socio-economic pathways.

Should coastal planners have concern over where land ice is melting?

PubMed Central

Larour, Eric; Ivins, Erik R.; Adhikari, Surendra

2017-01-01

There is a general consensus among Earth scientists that melting of land ice greatly contributes to sea-level rise (SLR) and that future warming will exacerbate the risks posed to human civilization. As land ice is lost to the oceans, both the Earth’s gravitational and rotational potentials are perturbed, resulting in strong spatial patterns in SLR, termed sea-level fingerprints. We lack robust forecasting models for future ice changes, which diminishes our ability to use these fingerprints to accurately predict local sea-level (LSL) changes. We exploit an advanced mathematical property of adjoint systems and determine the exact gradient of sea-level fingerprints with respect to local variations in the ice thickness of all of the world’s ice drainage systems. By exhaustively mapping these fingerprint gradients, we form a new diagnosis tool, henceforth referred to as gradient fingerprint mapping (GFM), that readily allows for improved assessments of future coastal inundation or emergence. We demonstrate that for Antarctica and Greenland, changes in the predictions of inundation at major port cities depend on the location of the drainage system. For example, in London, GFM shows LSL that is significantly affected by changes on the western part of the Greenland Ice Sheet (GrIS), whereas in New York, LSL change predictions are greatly sensitive to changes in the northeastern portions of the GrIS. We apply GFM to 293 major port cities to allow coastal planners to readily calculate LSL change as more reliable predictions of cryospheric mass changes become available. PMID:29152565

Biodiversity scenarios neglect future land-use changes.

PubMed

Titeux, Nicolas; Henle, Klaus; Mihoub, Jean-Baptiste; Regos, Adrián; Geijzendorffer, Ilse R; Cramer, Wolfgang; Verburg, Peter H; Brotons, Lluís

2016-07-01

Efficient management of biodiversity requires a forward-looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land-use and land-cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land-use and land-cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward-looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge. © 2016 John Wiley & Sons Ltd.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Climate change and socio-economic scenarios, land use modelling implications on water resources in an inner alpine area, Switzerland

NASA Astrophysics Data System (ADS)

Rey, Emmanuel; Schneider, Flurina; Liniger, Hanspeter; Weingartner, Rolf; Herweg, Karl

2014-05-01

The MontanAqua project aims to study the water resources management in the region Sierre-Montana (Valais, Switzerland). Land use is known to have an influence on the water resources (soil moisture dynamic, soil sealing, surface runoff and deep percolation). Thus land use modelling is of importance for the water resources management. An actual land use map was produced using infrared imagery (Niklaus 2012, Fig.1). Land use changes are known to be mainly drived by socio-economic factors as well as climatic factors (Dolman et al. 2003). Potential future Land uses was separatly predicted according to 1-. socio-economic and 2-. climatic/abiotic drivers : 1. 4 socio-economic scenarios were developped with stakeholders (Schneider et al. 2013) between 2010 and 2012. We modeled those socio-economic scenarios into a GIS application using Python programming (ModelBuilder in ArcGIS 10) to get a cartographic transcription of the wishes of the stakeholders for their region in 2050. 2. Uncorrelated climatic and abiotic drivers were used in a BIOMOD2 (Georges et al. 2013) framework. 4 models were used: Maximum Entropy (MAXENT), Multiple Adaptive Regression Splines (MARS), Classification Tree Analysis (CTA) and the Flexible Discriminant Analysis (FDA) to predict grassland, alpine pasture, vineyards and forest in our study region. Climatic scenarios were then introduced into the models to predict potential land use in 2050 driven only by climatic and abiotic factors The comparison of all the outputs demonstrates that the socio-economic drivers will have a more important impact in the region than the climatic drivers (e.g. -70% grassland surface for the worst socio-economic scenario vs. -40% of grassland surface for the worst climatic models). Further analysis also brings out the sensitivity of the grassland/alpine pasture system to the climate change and to socio-economic changes. Future work will be to cross the different land use maps obtained by the two model types and to use them to implement soil moisture and evaporation data for the near-future in the region Sierre-Montana. REFERENCES Niklaus M. 2012. An Object-oriented Approach for Mapping Current Land Use/Land Cover in the Study Area Crans-Montana-Sierre, Valais. MSc, Geography Institute, University of Bern Dolman A.J., Verhagen A. & Rovers C.A. 2003. Global environmental change and land use. Kluwer Academic Publisher. Dordrecht. Schneider F. & Rist S. 2013. Envisioning sustainable water futures in a transdisciplinary learning process: combining normative, explorative, and participatory scenario approaches. Sustainability Science, in press. Georges D. & Thuiller W. 2012. An example of species distribution modelling with biomod2. biomod2 version : 2.0.17

An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area

USGS Publications Warehouse

Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy

1994-01-01

Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.

Integrated Decision Tools for Sustainable Watershed/Ground Water and Crop Health using Predictive Weather, Remote Sensing, and Irrigation Decision Tools

NASA Astrophysics Data System (ADS)

Jones, A. S.; Andales, A.; McGovern, C.; Smith, G. E. B.; David, O.; Fletcher, S. J.

2017-12-01

US agricultural and Govt. lands have a unique co-dependent relationship, particularly in the Western US. More than 30% of all irrigated US agricultural output comes from lands sustained by the Ogallala Aquifer in the western Great Plains. Six US Forest Service National Grasslands reside within the aquifer region, consisting of over 375,000 ha (3,759 km2) of USFS managed lands. Likewise, National Forest lands are the headwaters to many intensive agricultural regions. Our Ogallala Aquifer team is enhancing crop irrigation decision tools with predictive weather and remote sensing data to better manage water for irrigated crops within these regions. An integrated multi-model software framework is used to link irrigation decision tools, resulting in positive management benefits on natural water resources. Teams and teams-of-teams can build upon these multi-disciplinary multi-faceted modeling capabilities. For example, the CSU Catalyst for Innovative Partnerships program has formed a new multidisciplinary team that will address "Rural Wealth Creation" focusing on the many integrated links between economic, agricultural production and management, natural resource availabilities, and key social aspects of govt. policy recommendations. By enhancing tools like these with predictive weather and other related data (like in situ measurements, hydrologic models, remotely sensed data sets, and (in the near future) linking to agro-economic and life cycle assessment models) this work demonstrates an integrated data-driven future vision of inter-meshed dynamic systems that can address challenging multi-system problems. We will present the present state of the work and opportunities for future involvement.

Future distribution of tundra refugia in northern Alaska

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Payer, David C.; Cook, Joseph A.; Talbot, Sandra L.

2013-01-01

Climate change in the Arctic is a growing concern for natural resource conservation and management as a result of accelerated warming and associated shifts in the distribution and abundance of northern species. We introduce a predictive framework for assessing the future extent of Arctic tundra and boreal biomes in northern Alaska. We use geo-referenced museum specimens to predict the velocity of distributional change into the next century and compare predicted tundra refugial areas with current land-use. The reliability of predicted distributions, including differences between fundamental and realized niches, for two groups of species is strengthened by fossils and genetic signatures of demographic shifts. Evolutionary responses to environmental change through the late Quaternary are generally consistent with past distribution models. Predicted future refugia overlap managed areas and indicate potential hotspots for tundra diversity. To effectively assess future refugia, variable responses among closely related species to climate change warrants careful consideration of both evolutionary and ecological histories.

Status and future transition of rapid urbanizing landscape in central Western Ghats - CA based approach

NASA Astrophysics Data System (ADS)

Bharath, S..; Rajan, K. S.; Ramachandra, T. V.

2014-11-01

The land use changes in forested landscape are highly complex and dynamic, affected by the natural, socio-economic, cultural, political and other factors. The remote sensing (RS) and geographical information system (GIS) techniques coupled with multi-criteria evaluation functions such as Markov-cellular automata (CA-Markov) model helps in analysing intensity, extent and future forecasting of human activities affecting the terrestrial biosphere. Karwar taluk of Central Western Ghats in Karnataka state, India has seen rapid transitions in its forest cover due to various anthropogenic activities, primarily driven by major industrial activities. A study based on Landsat and IRS derived data along with CA-Markov method has helped in characterizing the patterns and trends of land use changes over a period of 2004-2013, expected transitions was predicted for a set of scenarios through 2013-2022. The analysis reveals the loss of pristine forest cover from 75.51% to 67.36% (1973 to 2013) and increase in agriculture land as well as built-up area of 8.65% (2013), causing impact on local flora and fauna. The other factors driving these changes are the aggregated level of demand for land, local and regional effects of land use activities such as deforestation, improper practices in expansion of agriculture and infrastructure development, deteriorating natural resources availability. The spatio temporal models helped in visualizing on-going changes apart from prediction of likely changes. The CA-Markov based analysis provides us insights into the localized changes impacting these regions and can be useful in developing appropriate mitigation management approaches based on the modelled future impacts. This necessitates immediate measures for minimizing the future impacts.

Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales

NASA Astrophysics Data System (ADS)

Villarini, G.; Slater, L. J.; Salvi, K. A.

2017-12-01

Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

NASA Astrophysics Data System (ADS)

Li, Xia; Mitra, Chandana; Dong, Li; Yang, Qichun

2018-02-01

To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.

Predicting Future Training Opportunities Using the Land-Use Evolution and Impact Assessment Model

DTIC Science & Technology

2007-10-01

not require surveys of local populations or other time-intensive data gathering methods. ERDC/CERL SR-07-15 3 board records, local chamber of commerce records...neighbor, Fort Benning has been identified as an Army installation threatened by encroachment (Fort Benning 2004; Greater Columbus Georgia Chamber of Commerce 2004...worked with the Greater Columbus Consolidated Chamber of Commerce to create a Joint Land Use (JLUS) plan intended to implement buffer zones, land

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

Methods for predicting unsteady takeoff and landing trajectories of the aircraft

NASA Astrophysics Data System (ADS)

Shevchenko, A.; Pavlov, B.; Nachinkina, G.

2017-01-01

Informational and situational awareness of the aircrew greatly affects the probability of accidents, during takeoff and landing in particular. For the purpose of assessing the current and predicting the future states of an aircraft the energy approach to the flight control is used. Key energy balance equation is generalized to the ground phases. The equation describes the process of accumulating of the total energy of the aircraft along the entire trajectory, including the segment ahead. This segment length is defined by the required terminal energy state. For the takeoff phase the predict algorithm calculates the aircraft position on a runway after which it is possible to accelerate up to the speed of steady level flight and to reach the altitude sufficient for overcoming the high-rise obstacles. For the landing phase the braking distance length is determined. For increasing the likelihood of predicting the correction of the algorithm is introduced. The results of modeling many takeoffs and landings of passenger liner with different weights with the ahead obstacle and the engine failure are given. Working availability of the algorithm correction is shown.

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Mapping forest conditions: past, present, and future

Treesearch

Maggi Kelly

2017-01-01

Mapping and mapped data have always been critical to public land managers and researchers for identifying and characterizing wildlife habitat across scales, monitoring species and habitat change, and predicting and planning future scenarios. Maps and mapping protocols are often incorporated into wildlife and habitat management plans, as is the case with the California...

Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss

PubMed Central

Syphard, Alexandra D.; Bar Massada, Avi; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction. PMID:23977120

Human deforestation outweighs future climate change impacts of sedimentation on coral reefs

PubMed Central

Maina, Joseph; de Moel, Hans; Zinke, Jens; Madin, Joshua; McClanahan, Tim; Vermaat, Jan E.

2013-01-01

Near-shore coral reef systems are experiencing increased sediment supply due to conversion of forests to other land uses. Counteracting increased sediment loads requires an understanding of the relationship between forest cover and sediment supply, and how this relationship might change in the future. Here we study this relationship by simulating river flow and sediment supply in four watersheds that are adjacent to Madagascar’s major coral reef ecosystems for a range of future climate change projections and land-use change scenarios. We show that by 2090, all four watersheds are predicted to experience temperature increases and/or precipitation declines that, when combined, result in decreases in river flow and sediment load. However, these climate change-driven declines are outweighed by the impact of deforestation. Consequently, our analyses suggest that regional land-use management is more important than mediating climate change for influencing sedimentation of Malagasy coral reefs. PMID:23736941

Human deforestation outweighs future climate change impacts of sedimentation on coral reefs.

PubMed

Maina, Joseph; de Moel, Hans; Zinke, Jens; Madin, Joshua; McClanahan, Tim; Vermaat, Jan E

2013-01-01

Near-shore coral reef systems are experiencing increased sediment supply due to conversion of forests to other land uses. Counteracting increased sediment loads requires an understanding of the relationship between forest cover and sediment supply, and how this relationship might change in the future. Here we study this relationship by simulating river flow and sediment supply in four watersheds that are adjacent to Madagascar's major coral reef ecosystems for a range of future climate change projections and land-use change scenarios. We show that by 2090, all four watersheds are predicted to experience temperature increases and/or precipitation declines that, when combined, result in decreases in river flow and sediment load. However, these climate change-driven declines are outweighed by the impact of deforestation. Consequently, our analyses suggest that regional land-use management is more important than mediating climate change for influencing sedimentation of Malagasy coral reefs.

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE PAGES

Li, Xia; Mitra, Chandana; Dong, Li; ...

2017-02-02

In order to explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Our results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under themore » urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. Our study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.« less

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xia; Mitra, Chandana; Dong, Li

In order to explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Our results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under themore » urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. Our study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.« less

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xia; Mitra, Chandana; Dong, Li

To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, butmore » expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region. (C) 2017 Elsevier Ltd. All rights reserved.« less

Dynamic modeling of Tampa Bay urban development using parallel computing

USGS Publications Warehouse

Xian, G.; Crane, M.; Steinwand, D.

2005-01-01

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

Trends in continental temperature and humidity directly linked to ocean warming.

PubMed

Byrne, Michael P; O'Gorman, Paul A

2018-05-08

In recent decades, the land surface has warmed substantially more than the ocean surface, and relative humidity has fallen over land. Amplified warming and declining relative humidity over land are also dominant features of future climate projections, with implications for climate-change impacts. An emerging body of research has shown how constraints from atmospheric dynamics and moisture budgets are important for projected future land-ocean contrasts, but these ideas have not been used to investigate temperature and humidity records over recent decades. Here we show how both the temperature and humidity changes observed over land between 1979 and 2016 are linked to warming over neighboring oceans. A simple analytical theory, based on atmospheric dynamics and moisture transport, predicts equal changes in moist static energy over land and ocean and equal fractional changes in specific humidity over land and ocean. The theory is shown to be consistent with the observed trends in land temperature and humidity given the warming over ocean. Amplified land warming is needed for the increase in moist static energy over drier land to match that over ocean, and land relative humidity decreases because land specific humidity is linked via moisture transport to the weaker warming over ocean. However, there is considerable variability about the best-fit trend in land relative humidity that requires further investigation and which may be related to factors such as changes in atmospheric circulations and land-surface properties.

Effects of land use change on soil carbon cycling in the conterminous United States from 1900 to 2050

Treesearch

Peter B. Woodbury; Linda S. Heath; James E. Smith

2007-01-01

We developed matrices representing historical area transitions between forest and other land uses. We projected future transitions on the basis of historical transitions and econometric model results. These matrices were used to drive a model of changes in soil and forest floor carbon stocks. Our model predicted net carbon emission from 1900 until 1982, then...

Global environmental change effects on ecosystems: the importance of land-use legacies.

PubMed

Perring, Michael P; De Frenne, Pieter; Baeten, Lander; Maes, Sybryn L; Depauw, Leen; Blondeel, Haben; Carón, María M; Verheyen, Kris

2016-04-01

One of the major challenges in ecology is to predict how multiple global environmental changes will affect future ecosystem patterns (e.g. plant community composition) and processes (e.g. nutrient cycling). Here, we highlight arguments for the necessary inclusion of land-use legacies in this endeavour. Alterations in resources and conditions engendered by previous land use, together with influences on plant community processes such as dispersal, selection, drift and speciation, have steered communities and ecosystem functions onto trajectories of change. These trajectories may be modulated by contemporary environmental changes such as climate warming and nitrogen deposition. We performed a literature review which suggests that these potential interactions have rarely been investigated. This crucial oversight is potentially due to an assumption that knowledge of the contemporary state allows accurate projection into the future. Lessons from other complex dynamic systems, and the recent recognition of the importance of previous conditions in explaining contemporary and future ecosystem properties, demand the testing of this assumption. Vegetation resurvey databases across gradients of land use and environmental change, complemented by rigorous experiments, offer a means to test for interactions between land-use legacies and multiple environmental changes. Implementing these tests in the context of a trait-based framework will allow biologists to synthesize compositional and functional ecosystem responses. This will further our understanding of the importance of land-use legacies in determining future ecosystem properties, and soundly inform conservation and restoration management actions. © 2015 John Wiley & Sons Ltd.

Assessing the sensitivity of avian species abundance to land cover and climate

USGS Publications Warehouse

LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.

2016-01-01

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

Modeling the effects of climatic and land use changes on phytoplankton and water quality of the largest Turkish freshwater lake: Lake Beyşehir.

PubMed

Bucak, Tuba; Trolle, Dennis; Tavşanoğlu, Ü Nihan; Çakıroğlu, A İdil; Özen, Arda; Jeppesen, Erik; Beklioğlu, Meryem

2018-04-15

Climate change and intense land use practices are the main threats to ecosystem structure and services of Mediterranean lakes. Therefore, it is essential to predict the future changes and develop mitigation measures to combat such pressures. In this study, Lake Beyşehir, the largest freshwater lake in the Mediterranean basin, was selected to study the impacts of climate change and various land use scenarios on the ecosystem dynamics of Mediterranean freshwater ecosystems and the services that they provide. For this purpose, we linked catchment model outputs to the two different processed-based lake models: PCLake and GLM-AED, and tested the scenarios of five General Circulation Models, two Representation Concentration Pathways and three different land use scenarios, which enable us to consider the various sources of uncertainty. Climate change and land use scenarios generally predicted strong future decreases in hydraulic and nutrient loads from the catchment to the lake. These changes in loads translated into alterations in water level as well as minor changes in chlorophyll a (Chl-a) concentrations. We also observed an increased abundance of cyanobacteria in both lake models. Total phosphorus, temperature and hydraulic loading were found to be the most important variables determining cyanobacteria biomass. As the future scenarios revealed only minor changes in Chl-a due to the significant decrease in nutrient loads, our results highlight that reduced nutrient loading in a warming world may play a crucial role in offsetting the effects of temperature on phytoplankton growth. However, our results also showed increased abundance of cyanobacteria in the future may threaten ecosystem integrity and may limit drinking water ecosystem services. In addition, extended periods of decreased hydraulic loads from the catchment and increased evaporation may lead to water level reductions and may diminish the ecosystem services of the lake as a water supply for irrigation and drinking water. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

EPA Pesticide Factsheets

Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Development of a framework for quantifying the environmental impacts of urban development and construction practices.

PubMed

Li, Ke; Zhang, Peng; Crittenden, John C; Guhathakurta, Subhrajit; Chen, Yongsheng; Fernando, Harindra; Sawhney, Anil; McCartney, Peter; Grimm, Nancy; Kahhat, Ramzy; Joshi, Himanshu; Konjevod, Goran; Choi, Yu-Jin; Fonseca, Ernesto; Allenby, Braden; Gerrity, Daniel; Torrens, Paul M

2007-07-15

To encourage sustainable development, engineers and scientists need to understand the interactions among social decision-making, development and redevelopment, land, energy and material use, and their environmental impacts. In this study, a framework that connects these interactions was proposed to guide more sustainable urban planning and construction practices. Focusing on the rapidly urbanizing setting of Phoenix, Arizona, complexity models and deterministic models were assembled as a metamodel, which is called Sustainable Futures 2100 and were used to predict land use and development, to quantify construction material demands, to analyze the life cycle environmental impacts, and to simulate future ground-level ozone formation.

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Heiser, Mark

1999-01-01

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Forecasting and Predicting Coastal Local Sea Level as Support for Coastal Zone Management Decisions and Policy Making (Invited)

NASA Astrophysics Data System (ADS)

Plag, H.

2009-12-01

Local Sea Level (LSL) rise is one of the major anticipated impacts of future global warming with potentially devastating consequences, particularly in many low-lying, often subsiding, and densely populated coastal areas. Risk and vulnerability assessments in support of informed decisions ask for predictions of the plausible range of future LSL trajectories as input, while mitigation and adaptation to potentially rapid LSL changes would benefit from a forecasting of LSL changes on decadal time scales. Low-frequency to secular changes in LSL are the result of a number of location-dependent processes including ocean temperature and salinity changes, ocean and atmospheric circulation changes, mass exchange of the oceans with other reservoirs in the water cycle, and vertical land motion. Mass exchange between oceans and the ice sheets, glaciers, and land water storage has the potential to change coastal LSL in many geographical regions. LSL changes in response to mass exchange with land-based ice sheets, glaciers and water storage are spatially variable due to vertical land motion induced by the shifting loads and gravitational effects resulting from both the relocation of surface water mass and the deformation of the solid Earth under the load. As a consequence, close to a melting ice mass LSL will fall significantly and far away increase more than the global average. The so-called sea level equation expresses LSL as a function of current and past mass changes in ice sheets, glaciers, land water storage, and the resulting mass redistribution in the oceans. Predictions of mass-induced LSL changes exhibit significant inter-model differences, which introduce a large uncertainty in the prediction of LSL variations caused by changes in ice sheets, glaciers, and land water storage. Together with uncertainties in other contributions, this uncertainty produces a large range of plausible future LSL trajectories, which hampers the development of reasonable adaptation strategies for the coastal zone. While the sea level equation has been tested extensively in postglacial rebound studies for the viscous (post-mass change) contribution, a thorough validation of the elastic (co-mass change) contribution has yet to be done. Accurate observations of concurrent LSL changes, vertical land motion, and gravity changes required for such a test were missing until very recently. For the validation, new observations of LSL changes, vertical land motion, and gravity changes close to rapidly changing ice sheets and glaciers in Greenland, Svalbard, and other regions, as well as satellite altimetry observations of sea surface height changes and satellite gravity mission observations of mass changes in the hydrosphere are now available. With a validated solution, we will be able to better characterize LSL changes due to mass exchange of the oceans with, in particular, ice sheets and glaciers as an important contribution to the plausible range of future LSL trajectories in coastal zones. The current "error budget" will be assessed, and the impact of the uncertainties in LSL forecasts (on decadal time scales) and long-term projections (century time scales) on adaptation and mitigation strategies will be discussed.

How will SOA change in the future?: SOA IN THE FUTURE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Guangxing; Penner, Joyce E.; Zhou, Cheng

2016-02-17

Secondary organic aerosol (SOA) plays a significant role in the Earth system by altering its radiative balance. Here we use an Earth system model coupled with an explicit SOA formation module to estimate the response of SOA concentrations to changes in climate, anthropogenic emissions, and human land use in the future. We find that climate change is the major driver for SOA change under the representative concentration pathways for the 8.5 future scenario. Climate change increases isoprene emission rate by 18% with the effect of temperature increases outweighing that of the CO2 inhibition effect. Annual mean global SOA mass ismore » increased by 25% as a result of climate change. However, anthropogenic emissions and land use change decrease SOA. The net effect is that future global SOA burden in 2100 is nearly the same as that of the present day. The SOA concentrations over the Northern Hemisphere are predicted to decline in the future due to the control of sulfur emissions.« less

Choice of scale for integrating land use in malaria risk monitoring

NASA Astrophysics Data System (ADS)

Spangler, K. R.; Zaitchik, B. F.; Pan, W.; Vittor, A.; Patz, J.

2011-12-01

There were nearly 37,000 reported cases of malaria in Peru in 2009 alone. With over 30% of the population identified as being at "high risk" for exposure, detailed risk mapping, along with early detection and warning systems, are in critical need. While there is evidence that the increased formation of puddles arising from deforestation increases the breeding of the rainforest's primary malaria vector, Anopheles darlingi, neither the spatial structure of land uses/land cover changes (LUCC) nor the area of influence of LUCC on mosquito density has been systematically addressed. The radius of influence that LUCC - particularly areas of deforested land and other regions likely to see increases in stagnant water formation - has on mosquito presence is of particular importance, both for the design of warning systems and to inform future malaria transmission studies. Here, we present the results of satellite-based analysis of land use patterns and mosquito density along the Iquitos-Nauta road in the Peruvian Amazon. Comparing supervised classifications of Landsat images of the Iquitos region from 1996 and 2001 , land cover features around each of 832 mosquito sites were tabulated by percent at six different radii: 250m, 500m, 1000m, 2000m, 3000m, and 5000m. These results were then used as inputs in a mosquito prediction model that determined the most pertinent spatial scale necessary to predict both adult and larvae Anopheles mosquitoes (darlingi, benerocchi, oswaldoi, mattogrossenis, and rangeli). The application of this study is to provide a systematic means of determining which areas are at the highest risk of malaria infection in order to inform design of warning systems and future studies of land use and malaria in the Amazonian frontier.

Integrated dynamic landscape analysis and modeling system (IDLAMS) : installation manual.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Z.; Majerus, K. A.; Sundell, R. C.

The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) is a prototype, integrated land management technology developed through a joint effort between Argonne National Laboratory (ANL) and the US Army Corps of Engineers Construction Engineering Research Laboratories (USACERL). Dr. Ronald C. Sundell, Ms. Pamela J. Sydelko, and Ms. Kimberly A. Majerus were the principal investigators (PIs) for this project. Dr. Zhian Li was the primary software developer. Dr. Jeffrey M. Keisler, Mr. Christopher M. Klaus, and Mr. Michael C. Vogt developed the decision analysis component of this project. It was developed with funding support from the Strategic Environmental Research andmore » Development Program (SERDP), a land/environmental stewardship research program with participation from the US Department of Defense (DoD), the US Department of Energy (DOE), and the US Environmental Protection Agency (EPA). IDLAMS predicts land conditions (e.g., vegetation, wildlife habitats, and erosion status) by simulating changes in military land ecosystems for given training intensities and land management practices. It can be used by military land managers to help predict the future ecological condition for a given land use based on land management scenarios of various levels of training intensity. It also can be used as a tool to help land managers compare different land management practices and further determine a set of land management activities and prescriptions that best suit the needs of a specific military installation.« less

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

Medium density fiberboard made from Eucalyptus saligna

Treesearch

Andrzej M. Krzysik; James H. Muehl; John A. Youngquist; Fabio Spina Franca

2001-01-01

The production of industrial wood from natural forests is predicted to decline in the future. Factors that will contribute to this decline include changes in land use patterns, depletion of resources in some parts of the world, and the withdrawal of...

Idaho forest carbon projections from 2017 to 2117 under forest disturbance and climate change scenarios

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Crookston, N.; Kennedy, R. E.; Domke, G. M.; Fekety, P.; Falkowski, M. J.

2017-12-01

Commercial off-the-shelf lidar collections associated with tree measures in field plots allow aboveground biomass (AGB) estimation with high confidence. Predictive models developed from such datasets are used operationally to map AGB across lidar project areas. We use a random selection of these pixel-level AGB predictions as training for predicting AGB annually across Idaho and western Montana, primarily from Landsat time series imagery processed through LandTrendr. At both the landscape and regional scales, Random Forests is used for predictive AGB modeling. To project future carbon dynamics, we use Climate-FVS (Forest Vegetation Simulator), the tree growth engine used by foresters to inform forest planning decisions, under either constant or changing climate scenarios. Disturbance data compiled from LandTrendr (Kennedy et al. 2010) using TimeSync (Cohen et al. 2010) in forested lands of Idaho (n=509) and western Montana (n=288) are used to generate probabilities of disturbance (harvest, fire, or insect) by land ownership class (public, private) as well as the magnitude of disturbance. Our verification approach is to aggregate the regional, annual AGB predictions at the county level and compare them to annual county-level AGB summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. This analysis shows that when federal lands are disturbed the magnitude is generally high and when other lands are disturbed the magnitudes are more moderate. The probability of disturbance in corporate lands is higher than in other lands but the magnitudes are generally lower. This is consistent with the much higher prevalence of fire and insects occurring on federal lands, and greater harvest activity on private lands. We found large forest carbon losses in drier southern Idaho, only partially offset by carbon gains in wetter northern Idaho, due to anticipated climate change. Public and private forest managers can use these forest carbon projections to 2117 to inform 2017 decisions on which tree species and seed sources to select for planting, and implement forest management strategies now that may seek to maximize forest carbon sequestration for greenhouse gas abatement a century from now.

Evaluating hydrological response to forecasted land-use change—scenario testing with the automated geospatial watershed assessment (AGWA) tool

USGS Publications Warehouse

Kepner, William G.; Semmens, Darius J.; Hernandez, Mariano; Goodrich, David C.

2009-01-01

Envisioning and evaluating future scenarios has emerged as a critical component of both science and social decision-making. The ability to assess, report, map, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions to maintain the sustainable nature of our ecosystem services now and into the future. During the past two decades, important advances in the integration of remote imagery, computer processing, and spatial-analysis technologies have been used to develop landscape information that can be integrated with hydrologic models to determine long-term change and make predictive inferences about the future. Two diverse case studies in northwest Oregon (Willamette River basin) and southeastern Arizona (San Pedro River) were examined in regard to future land use scenarios relative to their impact on surface water conditions (e.g., sediment yield and surface runoff) using hydrologic models associated with the Automated Geospatial Watershed Assessment (AGWA) tool. The base reference grid for land cover was modified in both study locations to reflect stakeholder preferences 20 to 60 yrs into the future, and the consequences of landscape change were evaluated relative to the selected future scenarios. The two studies provide examples of integrating hydrologic modeling with a scenario analysis framework to evaluate plausible future forecasts and to understand the potential impact of landscape change on ecosystem services.

North American vegetation model for land-use planning in a changing climate: A solution to large classification problems

Treesearch

Gerald E. Rehfeldt; Nicholas L. Crookston; Cuauhtemoc Saenz-Romero; Elizabeth M. Campbell

2012-01-01

Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of...

How NASA Sees the Earth and Its Climate

NASA Technical Reports Server (NTRS)

BrowndeColstoun, Eric

2012-01-01

NASA Research Addresses Broad Questions: (1) How are global ecosystems changing? (2) What changes are occurring in global land cover and land use and what are their causes? (3) How is the Earth s surface being transformed and how can such information be used to predict future changes? (4) What are the consequences of land cover and land use change for the sustainability of ecosystems and economic productivity? NASA uses the view from above to monitor our changing home. Different satellites help us study the various systems of the Earth. No one system can do it all. NASA tools and science helps us to understand how the planet is changing and what the changes mean for us.

Land-use changes and the physical habitat of streams - a review with emphasis on studies within the U.S. Geological Survey Federal-State Cooperative Program

USGS Publications Warehouse

Jacobson, Robert B.; Femmer, Suzanne R.; McKenney, Rose A.

2001-01-01

Understanding the links between land-use changes and physical stream habitat responses is of increasing importance to guide resource management and stream restoration strategies. Transmission of runoff and sediment to streams can involve complex responses of drainage basins, including time lags, thresholds, and cumulative effects. Land-use induced runoff and sediment yield often combine with channel-scale disturbances that decrease flow resistance and erosion resistance, or increase stream energy. The net effects of these interactions on physical stream habitat—depth, velocity, substrate, cover, and temperature—are a challenge to predict. Improved diagnosis and predictive understanding of future change usually require multifaceted, multi-scale, and multidisciplinary studies based on a firm understanding of the history and processes operating in a drainage basin. The U.S. Geological Survey Federal-State Cooperative Program has been instrumental in fostering studies of the links between land use and stream habitat nationwide.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

A Prototype Land Information Sensor Web: Design, Implementation and Implication for the SMAP Mission

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Geiger, J. K.; Kumar, S. V.; Gates, L.

2009-12-01

Land Surface Model (LSM) predictions are regular in time and space, but these predictions are influenced by errors in model structure, input variables, parameters and inadequate treatment of sub-grid scale spatial variability. Consequently, LSM predictions are significantly improved through observation constraints made in a data assimilation framework. Several multi-sensor satellites are currently operating which provide multiple global observations of the land surface, and its related near-atmospheric properties. However, these observations are not optimal for addressing current and future land surface environmental problems. To meet future earth system science challenges, NASA will develop constellations of smart satellites in sensor web configurations which provide timely on-demand data and analysis to users, and can be reconfigured based on the changing needs of science and available technology. A sensor web is more than a collection of satellite sensors. That means a sensor web is a system composed of multiple platforms interconnected by a communication network for the purpose of performing specific observations and processing data required to support specific science goals. Sensor webs can eclipse the value of disparate sensor components by reducing response time and increasing scientific value, especially when the two-way interaction between the model and the sensor web is enabled. The study of a prototype Land Information Sensor Web (LISW) is sponsored by NASA, trying to integrate the Land Information System (LIS) in a sensor web framework which allows for optimal 2-way information flow that enhances land surface modeling using sensor web observations, and in turn allows sensor web reconfiguration to minimize overall system uncertainty. This prototype is based on a simulated interactive sensor web, which is then used to exercise and optimize the sensor web modeling interfaces. The Land Information Sensor Web Service-Oriented Architecture (LISW-SOA) has been developed and it is the very first sensor web framework developed especially for the land surface studies. Synthetic experiments based on the LISW-SOA and the virtual sensor web provide a controlled environment in which to examine the end-to-end performance of the prototype, the impact of various sensor web design trade-offs and the eventual value of sensor webs for a particular prediction or decision support. In this paper, the design, implementation of the LISW-SOA and the implication for the Soil Moisture Active and Passive (SMAP) mission is presented. Particular attention is focused on examining the relationship between the economic investment on a sensor web (space and air borne, ground based) and the accuracy of the model predicted soil moisture, which can be achieved by using such sensor observations. The Study of Virtual Land Information Sensor Web (LISW) is expected to provide some necessary a priori knowledge for designing and deploying the next generation Global Earth Observing System of systems (GEOSS).

Historical Carbon Dioxide Emissions Caused by Land-Use Changes are Possibly Larger than Assumed

NASA Technical Reports Server (NTRS)

Arneth, A.; Sitch, S.; Pongratz, J.; Stocker, B. D.; Ciais, P.; Poulter, B.; Bayer, A. D.; Bondeau, A.; Calle, L.; Chini, L. P.;

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example

USGS Publications Warehouse

Reiners, William A.; Liu, S.; Gerow, K.G.; Keller, M.; Schimel, D.S.

2002-01-01

[1] The humid tropical zone is a major source area for N2O and NO emissions to the atmosphere. Local emission rates vary widely with local conditions, particularly land use practices which swiftly change with expanding settlement and changing market conditions. The combination of wide variation in emission rates and rapidly changing land use make regional estimation and future prediction of biogenic trace gas emission particularly difficult. This study estimates contemporary, historical, and future N2O and NO emissions from 0.5 million ha of northeastern Costa Rica, a well-documented region in the wet tropics undergoing rapid agricultural development. Estimates were derived by linking spatially distributed environmental data with an ecosystem simulation model in an ensemble estimation approach that incorporates the variance and covariance of spatially distributed driving variables. Results include measures of variance for regional emissions. The formation and aging of pastures from forest provided most of the past temporal change in N2O and NO flux in this region; future changes will be controlled by the degree of nitrogen fertilizer application and extent of intensively managed croplands.

Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example

NASA Astrophysics Data System (ADS)

Reiners, W. A.; Liu, S.; Gerow, K. G.; Keller, M.; Schimel, D. S.

2002-12-01

The humid tropical zone is a major source area for N2O and NO emissions to the atmosphere. Local emission rates vary widely with local conditions, particularly land use practices which swiftly change with expanding settlement and changing market conditions. The combination of wide variation in emission rates and rapidly changing land use make regional estimation and future prediction of biogenic trace gas emission particularly difficult. This study estimates contemporary, historical, and future N2O and NO emissions from 0.5 million ha of northeastern Costa Rica, a well-documented region in the wet tropics undergoing rapid agricultural development. Estimates were derived by linking spatially distributed environmental data with an ecosystem simulation model in an ensemble estimation approach that incorporates the variance and covariance of spatially distributed driving variables. Results include measures of variance for regional emissions. The formation and aging of pastures from forest provided most of the past temporal change in N2O and NO flux in this region; future changes will be controlled by the degree of nitrogen fertilizer application and extent of intensively managed croplands.

Climate change, agricultural insecticide exposure, and risk for freshwater communities.

PubMed

Kattwinkel, Mira; Kühne, Jan-Valentin; Foit, Kaarina; Liess, Matthias

2011-09-01

Climate change exerts direct effects on ecosystems but has additional indirect effects due to changes in agricultural practice. These include the increased use of pesticides, changes in the areas that are cultivated, and changes in the crops cultivated. It is well known that pesticides, and in particular insecticides, affect aquatic ecosystems adversely. To implement effective mitigation measures it is necessary to identify areas that are affected currently and those that will be affected in the future. As a consequence, we predicted potential exposure to insecticide (insecticide runoff potential, RP) under current conditions (1990) and under a model scenario of future climate and land use (2090) using a spatially explicit model on a continental scale, with a focus on Europe. Space-for-time substitution was used to predict future levels of insecticide application, intensity of agricultural land use, and cultivated crops. To assess the indirect effects of climate change, evaluation of the risk of insecticide exposure was based on a trait-based, climate-insensitive indicator system (SPEAR, SPEcies At Risk). To this end, RP and landscape characteristics that are relevant for the recovery of affected populations were combined to estimate the ecological risk (ER) of insecticides for freshwater communities. We predicted a strong increase in the application of, and aquatic exposure to, insecticides under the future scenario, especially in central and northern Europe. This, in turn, will result in a severe increase in ER in these regions. Hence, the proportion of stream sites adjacent to arable land that do not meet the requirements for good ecological status as defined by the EU Water Framework Directive will increase (from 33% to 39% for the EU-25 countries), in particular in the Scandinavian and Baltic countries (from 6% to 19%). Such spatially explicit mapping of risk enables the planning of adaptation and mitigation strategies including vegetated buffer strips and nonagricultural recolonization zones along streams.

Contributions of projected land use to global radiative forcing ascribed to local sources

NASA Astrophysics Data System (ADS)

Ward, D. S.; Mahowald, N. M.; Kloster, S.

2013-12-01

With global demand for food expected to dramatically increase and put additional pressures on natural lands, there is a need to understand the environmental impacts of land use and land cover change (LULCC). Previous studies have shown that the magnitude and even the sign of the radiative forcing (RF) of biogeophysical effects from LULCC depends on the latitude and forest ecology of the disturbed region. Here we ascribe the contributions to the global RF by land-use related anthropogenic activities to their local sources, organized on a grid of 1.9 degrees latitude by 2.5 degrees longitude. We use RF estimates for the year 2100, using five future LULCC projections, computed from simulations with the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. Our definition of the LULCC RF includes changes to terrestrial carbon storage, methane and nitrous oxide emissions, atmospheric chemistry, aerosol emissions, and surface albedo. We ascribe the RF to gridded locations based on LULCC-related emissions of relevant trace gases and aerosols, including emissions from fires. We find that the largest contributions to the global RF in year 2100 from LULCC originate in the tropics for all future scenarios. In fact, LULCC is the largest tropical source of anthropogenic RF. The LULCC RF in the tropics is dominated by emissions of CO2 from deforestation and methane emissions from livestock and soils. Land surface albedo change is rarely the dominant forcing agent in any of the future LULCC projections, at any location. By combining the five future scenarios we find that deforested area at a specific tropical location can be used to predict the contribution to global RF from LULCC at that location (the relationship does not hold as well in the extratropics). This information could support global efforts like REDD (Reducing Emissions from Deforestation and Forest Degradation), that aim to reduce greenhouse gas emissions from land use, by helping to optimize their effectiveness for climate change mitigation.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage.

PubMed

Chaplin-Kramer, Rebecca; Sharp, Richard P; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà I Canals, Llorenç; Eichelberger, Bradley A; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M

2015-06-16

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage

PubMed Central

Chaplin-Kramer, Rebecca; Sharp, Richard P.; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà i Canals, Llorenç; Eichelberger, Bradley A.; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M.

2015-01-01

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation. PMID:26082547

Forecasting relative impacts of land use on anadromous fish habitat to guide conservation planning.

PubMed

Lohse, Kathleen A; Newburn, David A; Opperman, Jeff J; Merenlender, Adina M

2008-03-01

Land use change can adversely affect water quality and freshwater ecosystems, yet our ability to predict how systems will respond to different land uses, particularly rural-residential development, is limited by data availability and our understanding of biophysical thresholds. In this study, we use spatially explicit parcel-level data to examine the influence of land use (including urban, rural-residential, and vineyard) on salmon spawning substrate quality in tributaries of the Russian River in California. We develop a land use change model to forecast the probability of losses in high-quality spawning habitat and recommend priority areas for incentive-based land conservation efforts. Ordinal logistic regression results indicate that all three land use types were negatively associated with spawning substrate quality, with urban development having the largest marginal impact. For two reasons, however, forecasted rural-residential and vineyard development have much larger influences on decreasing spawning substrate quality relative to urban development. First, the land use change model estimates 10 times greater land use conversion to both rural-residential and vineyard compared to urban. Second, forecasted urban development is concentrated in the most developed watersheds, which already have poor spawning substrate quality, such that the marginal response to future urban development is less significant. To meet the goals of protecting salmonid spawning habitat and optimizing investments in salmon recovery, we suggest investing in watersheds where future rural-residential development and vineyards threaten high-quality fish habitat, rather than the most developed watersheds, where land values are higher.

Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

NASA Astrophysics Data System (ADS)

Harun, R.

2013-05-01

This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the relative effectiveness of the two models, ANN and CA, in urban planning. The questions that are addressed in this research are: a) What makes ANN models different from CA models?; b) Which model has higher accuracy in predicting future urban land use change?; and c) Are the models effective enough in guiding urban land use policies and strategies? The models that are used for this research are Multilayer Perceptron (MLP) and CA model, available in IDRISI Taiga. Since, the objective is to perform a comparative analysis and draw general inferences irrespective of specific urban policies, the availability of data was given more emphasis over the selection of particular location. Urban area in Massachusetts was chosen to conduct the study due to data availability. Extensive literature review was performed to understand the functionality of the two models. The models were applied to predict future changes and the accuracy assessment was performed using standard matrix. Inferences were drawn about the applicability of the models in urban planning context along with recommendations. This research will not only develop understanding of land use models among urban planners, but also will create an environment of coupled research between planners and modellers.

Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment

NASA Astrophysics Data System (ADS)

Parkin, G.; O'Donnell, G.; Ewen, J.; Bathurst, J. C.; O'Connell, P. E.; Lavabre, J.

1996-02-01

Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583-594) designed to address these types of application; the method involves making 'blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.

Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models.

PubMed

Tildesley, Michael J; Ryan, Sadie J

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

PubMed Central

Tildesley, Michael J.; Ryan, Sadie J.

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock. PMID:23133352

Do changes in climate and land use pose a risk to the future water availability of Mediterranean Lakes?

NASA Astrophysics Data System (ADS)

Bucak, T.; Trolle, D.; Andersen, H. E.; Thodsen, H.; Erdoğan, Ş.; Levi, E. E.; Filiz, N.; Jeppesen, E.; Beklioğlu, M.

2016-12-01

Inter- and intra-annual water level fluctuations and change in water flow regime are intrinsic characteristics of Mediterranean lakes. However, considering the climate change projections for the water-limited Mediterranean region where potential evapotranspiration exceeds precipitation and with increased air temperatures and decreased precipitation, more dramatic water level declines in lakes and severe water scarcity problems are expected to occur in the future. Our study lake, Lake Beyşehir, the largest freshwater lake in the Mediterranean basin, is - like other Mediterranean lakes - under pressure due to water abstraction for irrigated crop farming and climatic changes, and integrated water level management is therefore required. We used an integrated modeling approach to predict the future lake water level of Lake Beyşehir in response to the future changes in both climate and, potentially, land use by linking the catchment model Soil and Water Assessment Tool (SWAT) with a Support Vector Machine Regression model (ɛ-SVR). We found that climate change projections caused enhanced potential evapotranspiration and reduced total runoff, whereas the effects of various land use scenarios within the catchment were comparatively minor. In all climate scenarios applied in the ɛ-SVR model, changes in hydrological processes caused a water level reduction, predicting that the lake may dry out already in the 2040s with the current outflow regulation considering the most pessimistic scenario. Based on model runs with optimum outflow management, a 9-60% reduction in outflow withdrawal is needed to prevent the lake from drying out by the end of this century. Our results indicate that shallow Mediterranean lakes may face a severe risk of drying out and loss of ecosystem value in near future if the current intense water abstraction is maintained. Therefore, we conclude that outflow management in water-limited regions in a warmer and drier future and sustainable use of water sources are vitally important to sustain lake ecosystems and their ecosystem services.

The Role of Soil Water and Land Feedbacks in Decadal Drought in Western North America

NASA Astrophysics Data System (ADS)

Langford, S.; Chikamoto, Y.; Noone, D. C.

2013-12-01

Western North America is susceptible to severe impacts of megadroughts, as evidenced by tree-core or lake sediment records. Future predictions suggest that this region will become more arid, with further consequences for water resources. Understanding the mechanisms of drought variability and persistence in western North America is critical for the eventual development of effective forecasting methods. The ocean is expected to be the main source of decadal memory in the system as the atmosphere varies on a much shorter timescale. The ocean's role in driving the low-frequency variability of the system is potentially predictable. However, low-frequency precipitation anomalies in western North America can occur in the absence of ocean feedbacks. Sea surface temperature anomalies in the north Pacific Ocean only account for around 20 per cent of the low-frequency winter precipitation in California in the CMIP5 historical runs. This is not sufficient to use the skill of global coupled models in predicting ocean conditions ahead of time to successfully forecast the possibility of long-term drought in western North America. Megadroughts therefore may be generated by unpredictable atmospheric noise, or persisted by other sources of low-frequency variability such as land processes and feedbacks. Snowpack in western North America is a crucial water resource for the surrounding communities, storing the winter precipitation for use later in the year. Likewise, soil moisture integrates the precipitation signal; the time scale depends on the depth and characteristics of the soil. Water storage and related variables are more predictable on longer timescales than precipitation, as measured by anomaly correlation for hindcasts compared to a 'perfect model' control run with CESM1.0.3. The importance of antecedent land conditions in persisting megadroughts in western North America is explored with ensemble simulations of CESM1.0.3, where the atmosphere is perturbed at the initiation and peak of a megadrought in the control run. Numerical experiments are used to test land-atmosphere feedbacks or memory sources, highlighting the sensitivity of megadrought initiation, persistence and termination to these antecedent conditions. The model results confirm the importance of land processes in projections of future decadal hydroclimate.

Assessment method for epithermal gold deposits in Northeast Washington State using weights-of-evidence GIS modeling

USGS Publications Warehouse

Boleneus, D.E.; Raines, G.L.; Causey, J.D.; Bookstrom, A.A.; Frost, T.P.; Hyndman, P.C.

2001-01-01

The weights-of-evidence analysis, a quantitative mineral resource mapping tool, is used to delineate favorable areas for epithermal gold deposits and to predict future exploration activity of the mineral industry for similar deposits in a four-county area (222 x 277 km), including the Okanogan and Colville National Forests of northeastern Washington. Modeling is applied in six steps: (1) building a spatial digital database, (2) extracting predictive evidence for a particular deposit, based on an exploration model, (3) calculating relative weights for each predictive map, (4) combining the geologic evidence maps to predict the location of undiscovered mineral resources and (5) measuring the intensity of recent exploration activity by use of mining claims on federal lands, and (6) combining mineral resource and exploration activity into an assessment model of future mining activity. The analysis is accomplished on a personal computer using ArcView GIS platform with Spatial Analyst and Weights-of-Evidence software. In accord with the descriptive model for epithermal gold deposits, digital geologic evidential themes assembled include lithologic map units, thrust faults, normal faults, and igneous dikes. Similarly, geochemical evidential themes include placer gold deposits and gold and silver analyses from stream sediment (silt) samples from National Forest lands. Fifty mines, prospects, or occurrences of epithermal gold deposits, the training set, define the appropriate a really-associated terrane. The areal (or spatial) correlation of each evidential theme with the training set yield predictor theme maps for lithology, placer sites and normal faults. The weights-of-evidence analysis disqualified the thrust fault, dike, and gold and silver silt analyses evidential themes because they lacked spatial correlation with the training set. The decision to accept or reject evidential themes as predictors is assisted by considering probabilistic data consisting of weights and contrast values calculated for themes according to areal correlation with the training sites. Predictor themes having acceptable weights and contrast values are combined into a preliminary model to predict the locations of undiscovered epithermal gold deposits. This model facilitates ranking of tracts as non-permissive, permissive or favorable categories based on exclusionary, passive, and active criteria through evaluation of probabilistic data provided by interaction of predictor themes. The method is very similar to the visual inspection method of drawing conclusions from anomalies on a manually overlain system of maps. This method serves as a model for future mineral assessment procedures because of its objective nature. To develop a model to predict future exploration activity, the locations of lode mining claims were summarized for 1980, 1985, 1990, and 1996. Land parcels containing historic claims were identified either as those with mining claims present in 1980 or valid claims present in 1985. Current claim parcels were identified as those containing valid lode claims in either 1990 or 1996. A consistent parcel contains both historic and current claims. The epithermal gold and mining claim activity models were combined into an assessment (or mineral resource-activity) model to assist in land use decisions by providing a prediction of mineral exploration activity on federal land in the next decade. Ranks in the assessment model are: (1) no activity, (2) low activity, (3) low to moderate activity, (4) moderate activity and (5) high activity.

How to reduce the uncertainties in predictions of local coastal sea level as decision support: the contribution of GGOS

NASA Astrophysics Data System (ADS)

Plag, H.-P.

2009-04-01

Local Sea Level (LSL) rise is one of the major anticipated impacts of future global warming. In many low-lying and often subsiding coastal areas, an increase of local sea-surface height is likely to increase the hazards of storm surges and hurricances and to lead to major inundation. Single major disasters due to storm surges and hurricanes hitting densely populated urban areas are estimated to inflict losses in excess of 100 billion. Decision makers face a trade-off between imposing the very high costs of coastal protection, mitigation and adaptation upon today's national economies and leaving the costs of potential major disasters to future generations. Risk and vulnerability assessments in support of informed decisions require as input predictions of the range of future LSL rise with reliable estimates of uncertainties. Secular changes in LSL are the result of a mix of location-dependent factors including ocean temperature and salinity changes, ocean and atmospheric circulation changes, mass exchange of the ocean with terrestrial water storage and the cryosphere, and vertical land motion. Current aleatory uncertainties in observations relevant to past and current LSL changes combined with epistemic uncertainties in some of the forcing functions for LSL changes produce a large range of plausible future LSL trajectories. This large range hampers the development of reasonable mitigation and adaptation strategies in the coastal zone. A detailed analysis of the uncertainties helps to answer the question what and how observations could help to reduce the uncertainties. The analysis shows that the Global Geodetic Observing System (GGOS) provides valuable observations and products towards this goal. Observations of the large ice sheets can improve the constraints on the current mass balance of the cryosphere and support cryosphere model validation. Vertical land motion close to melting ice sheets are highly relevant in the validation of models for the elastic response of the Earth to glacial deloading. Combination of satellite gravity mission with ground-based observations of gravity and vertical land motion in areas with significant mass changes (both in cryosphere, land water storage, and ocean) could help to improve models of the global water and energy cycle, which ultimately improves the understanding of current LSL changes. For LSL projections, local vertical land motion given in a reference frame tied to the center of mass is an important input, which currently contributes significantly to the error budget of LSL predictions. Improvements of the terrestrial reference frame would reduce this error contribution.

Ecosystem Services in Agricultural Landscapes: A Spatially Explicit Approach to Support Sustainable Soil Management

PubMed Central

Crossman, Neville D.; MacEwan, Richard J.; Wallace, D. Dugal; Bennett, Lauren T.

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km2 in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes. PMID:24616632

Ecosystem services in agricultural landscapes: a spatially explicit approach to support sustainable soil management.

PubMed

Forouzangohar, Mohsen; Crossman, Neville D; MacEwan, Richard J; Wallace, D Dugal; Bennett, Lauren T

2014-01-01

Soil degradation has been associated with a lack of adequate consideration of soil ecosystem services. We demonstrate a broadly applicable method for mapping changes in the supply of two priority soil ecosystem services to support decisions about sustainable land-use configurations. We used a landscape-scale study area of 302 km(2) in northern Victoria, south-eastern Australia, which has been cleared for intensive agriculture. Indicators representing priority soil services (soil carbon sequestration and soil water storage) were quantified and mapped under both a current and a future 25-year land-use scenario (the latter including a greater diversity of land uses and increased perennial crops and irrigation). We combined diverse methods, including soil analysis using mid-infrared spectroscopy, soil biophysical modelling, and geostatistical interpolation. Our analysis suggests that the future land-use scenario would increase the landscape-level supply of both services over 25 years. Soil organic carbon content and water storage to 30 cm depth were predicted to increase by about 11% and 22%, respectively. Our service maps revealed the locations of hotspots, as well as potential trade-offs in service supply under new land-use configurations. The study highlights the need to consider diverse land uses in sustainable management of soil services in changing agricultural landscapes.

Building factorial regression models to explain and predict nitrate concentrations in groundwater under agricultural land

NASA Astrophysics Data System (ADS)

Stigter, T. Y.; Ribeiro, L.; Dill, A. M. M. Carvalho

2008-07-01

SummaryFactorial regression models, based on correspondence analysis, are built to explain the high nitrate concentrations in groundwater beneath an agricultural area in the south of Portugal, exceeding 300 mg/l, as a function of chemical variables, electrical conductivity (EC), land use and hydrogeological setting. Two important advantages of the proposed methodology are that qualitative parameters can be involved in the regression analysis and that multicollinearity is avoided. Regression is performed on eigenvectors extracted from the data similarity matrix, the first of which clearly reveals the impact of agricultural practices and hydrogeological setting on the groundwater chemistry of the study area. Significant correlation exists between response variable NO3- and explanatory variables Ca 2+, Cl -, SO42-, depth to water, aquifer media and land use. Substituting Cl - by the EC results in the most accurate regression model for nitrate, when disregarding the four largest outliers (model A). When built solely on land use and hydrogeological setting, the regression model (model B) is less accurate but more interesting from a practical viewpoint, as it is based on easily obtainable data and can be used to predict nitrate concentrations in groundwater in other areas with similar conditions. This is particularly useful for conservative contaminants, where risk and vulnerability assessment methods, based on assumed rather than established correlations, generally produce erroneous results. Another purpose of the models can be to predict the future evolution of nitrate concentrations under influence of changes in land use or fertilization practices, which occur in compliance with policies such as the Nitrates Directive. Model B predicts a 40% decrease in nitrate concentrations in groundwater of the study area, when horticulture is replaced by other land use with much lower fertilization and irrigation rates.

Effects of Land Use on the Predictability of Land-Atmosphere Fluxes and Moisture Transport in the North American Monsoon Region

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Mascaro, G.; White, D. D.; Vivoni, E. R.

2014-12-01

Southern Arizona and New Mexico receive 40-60% of their annual rainfall in the summer, as part of the North American Monsoon (NAM). Modeling studies suggest that 15-25% of this rainfall first falls on Mexican land, is transpired by vegetation, and subsequently is transported northward across the border to the US. The main source regions in Mexico include two primary landcover types in Sonora and Sinaloa: subtropical scrub and tropical deciduous forests in the foothills of the Sierra Madre Occidental; and large expanses of irrigated agriculture along the Gulf of California. The foothill ecosystems, known for their rapid greening and large transpiration rates at the onset of the monsoon, are under threat from deforestation for grazing activities. On the other hand, irrigated agriculture in both the winter and summer has shifted the seasonality of evaporative fluxes and introduced socio-economic factors into their interannual variability and predictability. In this study, we examine the differences in spatial and temporal characteristics of evapotranspiration yielded by current and pre-industrial land cover / land use. To this end, we employ the Variable Infiltration Capacity (VIC) land surface model at 1/16 degree resolution, driven by gridded meteorological observations and MODIS LAI, NDVI, and albedo products, across the NAM region (Arizona, New Mexico, and northern Mexico). We compare the magnitude and timing of land-atmosphere fluxes given by both pre-industrial and current land cover/use, as well as the land cover under several possible alternative land use scenarios. We identify the regions where the largest changes in magnitude and timing of evapotranspiration have occurred, as well as the regions and land use changes that could produce the largest changes in future evapotranspiration under different scenarios. Finally, we explore the consequences these effects have for the predictability of monsoon moisture transport.

Predicting the unpredictable: potential climate change impacts on vegetation in the Pacific Northwest

Treesearch

Marie Oliver; David W. Peterson; Becky Kerns

2016-01-01

Earth's climate is changing, as evidenced by warming temperatures, increased temperature variability, fluctuating precipitation patterns, and climate-related environmental disturbances. And with considerable uncertainty about the future, Forest Service land managers are now considering climate change adaptation in their planning efforts. They want practical...

Branching out: Agroforestry as a climate change mitigation and adaptation tool for agriculture

USDA-ARS?s Scientific Manuscript database

The United States and Canadian agricultural lands are being targeted to provide more environmental and economic services while at the same time their capacity to provide these services under potential climate change (CC) is being questioned. Predictions of future climate conditions include longer gr...

The Response of Fish Habitat to Environmental Flows in the Albemarle-Pamlico Watershed

EPA Science Inventory

The provision of habitat for fish is an important service provided by rivers. Future land development and climate change will likely alter several aspects of habitat, including flow. We have used hierarchical models to predict the presence of 25 fish species within the Albemarle-...

Effective Mitigation and Adaptation Strategies for Public Health Impacts of Heatwaves for Brookline, MA

NASA Astrophysics Data System (ADS)

Jalalzadeh Fard, B.; Hassanzadeh, H.; Bhatia, U.; Ganguly, A. R.

2016-12-01

Studies on urban areas show a significant increase in frequency and intensity of heatwaves over the past decades, and predict the same trend for future. Since heatwaves have been responsible for a large number of life losses, urgent adaptation and mitigation strategies are required in the policy and decision making level for a sustainable urban planning. The Sustainability and Data Sciences Laboratory at Northeastern University, under the aegis of Thriving Earth Exchange of AGU, is working with the town of Brookline to understand the potential public health impacts of anticipated heatwaves. We consider the most important social and physical factors to obtain vulnerability and exposure parameters for each census block group of the town. Utilizing remote sensing data, we locate Urban Heat Islands (UHIs) during a recent heatwave event, as the hazard parameter. We then create priority risk map using the risk framework. Our analyses show spatial correlations between the UHIs and social factors such as poverty, and physical factors such as land cover variations. Furthermore, we investigate the future heatwave frequency and intensity increases by analyzing the climate models predictions. For future changes of UHIs, land cover changes are investigated using available predictive data. Also, socioeconomic predictions are carried out to complete the futuristic models of heatwave risks. Considering plausible scenarios for Brookline, we develop different risk maps based on the vulnerability, exposure and hazard parameters. Eventually, we suggest guidelines for Heatwave Action Plans for prioritizing effective mitigation and adaptation strategies in urban planning for the town of Brookline.

Impact of Climate Change on Soil and Groundwater Chemistry Subject to Process Waste Land Application

NASA Astrophysics Data System (ADS)

McNab, W. W.

2013-12-01

Nonhazardous aqueous process waste streams from food and beverage industry operations are often discharged via managed land application in a manner designed to minimize impacts to underlying groundwater. Process waste streams are typically characterized by elevated concentrations of solutes such as ammonium, organic nitrogen, potassium, sodium, and organic acids. Land application involves the mixing of process waste streams with irrigation water which is subsequently applied to crops. The combination of evapotranspiration and crop salt uptake reduces the downward mass fluxes of percolation water and salts. By carefully managing application schedules in the context of annual climatological cycles, growing seasons, and process requirements, potential adverse environmental impacts to groundwater can be mitigated. However, climate change poses challenges to future process waste land application efforts because the key factors that determine loading rates - temperature, evapotranspiration, seasonal changes in the quality and quantity of applied water, and various crop factors - are all likely to deviate from current averages. To assess the potential impact of future climate change on the practice of land application, coupled process modeling entailing transient unsaturated fluid flow, evapotranspiration, crop salt uptake, and multispecies reactive chemical transport was used to predict changes in salt loading if current practices are maintained in a warmer, drier setting. As a first step, a coupled process model (Hydrus-1D, combined with PHREEQC) was calibrated to existing data sets which summarize land application loading rates, soil water chemistry, and crop salt uptake for land disposal of process wastes from a food industry facility in the northern San Joaquin Valley of California. Model results quantify, for example, the impacts of evapotranspiration on both fluid flow and soil water chemistry at shallow depths, with secondary effects including carbonate mineral precipitation and ion exchange. The calibrated model was then re-run assuming different evapotranspiration and crop growth regimes, and different seasonally-adjusted applied water compositions, to elucidate possible impacts to salt loading reactive chemistry. The results of the predictive modeling indicate the extent to which salts could be redistributed within the soil column as a consequence of climate change. The degree to which these findings are applicable to process waste land application operations at other sites was explored by varying the soil unsaturated flow parameters as a model sensitivity assessment. Taken together, the model results help to quantify operational changes to land application that may be necessary to avoid future adverse environmental impacts to soil and groundwater.

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Land use and climate change impacts on runoff and soil erosion at the hillslope scale in the Brazilian Cerrado.

PubMed

Anache, Jamil A A; Flanagan, Dennis C; Srivastava, Anurag; Wendland, Edson C

2018-05-01

Land use and climate change can influence runoff and soil erosion, threatening soil and water conservation in the Cerrado biome in Brazil. The adoption of a process-based model was necessary due to the lack of long-term observed data. Our goals were to calibrate the WEPP (Water Erosion Prediction Project) model for different land uses under subtropical conditions in the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change. We performed the model calibration using a 5-year dataset (2012-2016) of observed runoff and soil loss in four different land uses (wooded Cerrado, tilled fallow without plant cover, pasture, and sugarcane) in experimental plots. Selected soil and management parameters were optimized for each land use during the WEPP model calibration with the existing field data. The simulations were conducted using the calibrated WEPP model components with a 100-year climate dataset created with CLIGEN (weather generator) based on regional climate statistics. We obtained downscaled General Circulation Model (GCM) projections, and runoff and soil loss were predicted with WEPP using future climate scenarios for 2030, 2060, and 2090 considering different Representative Concentration Pathways (RCPs). The WEPP model had an acceptable performance for the subtropical conditions. Land use can influence runoff and soil loss rates in a significant way. Potential climate changes, which indicate the increase of rainfall intensities and depths, may increase the variability and rates of runoff and soil erosion. However, projected climate changes did not significantly affect the runoff and soil erosion for the four analyzed land uses at our location. Finally, the runoff behavior was distinct for each land use, but for soil loss we found similarities between pasture and wooded Cerrado, suggesting that the soil may attain a sustainable level when the land management follows conservation principles. Copyright © 2017 Elsevier B.V. All rights reserved.

A changing climate: impacts on human exposures to O3 using ...

EPA Pesticide Factsheets

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur

Optimal stomatal behaviour around the world

NASA Astrophysics Data System (ADS)

Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; Prentice, I. Colin; Wang, Han; Baig, Sofia; Eamus, Derek; de Dios, Victor Resco; Mitchell, Patrick; Ellsworth, David S.; de Beeck, Maarten Op; Wallin, Göran; Uddling, Johan; Tarvainen, Lasse; Linderson, Maj-Lena; Cernusak, Lucas A.; Nippert, Jesse B.; Ocheltree, Troy W.; Tissue, David T.; Martin-Stpaul, Nicolas K.; Rogers, Alistair; Warren, Jeff M.; de Angelis, Paolo; Hikosaka, Kouki; Han, Qingmin; Onoda, Yusuke; Gimeno, Teresa E.; Barton, Craig V. M.; Bennie, Jonathan; Bonal, Damien; Bosc, Alexandre; Löw, Markus; Macinins-Ng, Cate; Rey, Ana; Rowland, Lucy; Setterfield, Samantha A.; Tausz-Posch, Sabine; Zaragoza-Castells, Joana; Broadmeadow, Mark S. J.; Drake, John E.; Freeman, Michael; Ghannoum, Oula; Hutley, Lindsay B.; Kelly, Jeff W.; Kikuzawa, Kihachiro; Kolari, Pasi; Koyama, Kohei; Limousin, Jean-Marc; Meir, Patrick; Lola da Costa, Antonio C.; Mikkelsen, Teis N.; Salinas, Norma; Sun, Wei; Wingate, Lisa

2015-05-01

Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.

UK Environmental Prediction - integration and evaluation at the convective scale

NASA Astrophysics Data System (ADS)

Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

2016-04-01

It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. For example, high impact weather is typically manifested through various interactions and feedbacks between different components of the Earth System. Damaging high winds can lead to significant damage from the large waves and storm surge along coastlines. The impact of intense rainfall can be translated through saturated soils and land surface processes, high river flows and flooding inland. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system and discuss progress and initial results from further development to integrate wave interactions. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

The effects of changing land cover on streamflow simulation in Puerto Rico

USGS Publications Warehouse

Van Beusekom, Ashley E.; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Forecasting future phosphorus export to the Laurentian Great Lakes from land-derived nutrient inputs

NASA Astrophysics Data System (ADS)

LaBeau, M. B.; Robertson, D. M.; Mayer, A. S.; Pijanowski, B. C.

2011-12-01

Anthropogenic use of the land through agricultural and urban activities has significantly increased phosphorus loading to rivers that flow to the Great Lakes. Phosphorus (P) is a critical element in the eutrophication of the freshwater ecosystems, most notably the Great Lakes. To better understand factors influencing phosphorus delivery to aquatic systems and thus their potential harmful effects to lake ecosystems, models that predict P export should incorporate account for changing changes in anthropogenic activities. Land-derived P from high yielding sources, such as agriculture and urban areas, affect eutrophication at various scales (e.g. specific bays to all of Lake Erie). SPARROW (SPAtially Referenced Regression On Watershed attributes) is a spatially explicit watershed model that has been used to understand linkages between land-derived sources and nutrient transport to the Great Lakes. The Great Lakes region is expected to experience a doubling of urbanized areas along with a ten percent increase in agricultural use over the next 40 years, which is likely to increase P loading. To determine how these changes will impact P loading, SPARROW have been developed that relate changes in land use to changes in nutrient sources, including relationships between row crop acreage and fertilizer intensity and urban land use and point source intensity. We used land use projections from the Land Transformation Model, a, spatially explicit, neural-net based land change model. Land use patterns from current to 2040 were used as input into HydroSPARROW, a forecasting tool that enables SPARROW to simulate the effects of various land-use and climate scenarios. Consequently, this work is focusing on understanding the effects of how specific agriculture and urbanization activities affect P loading in the watersheds of the Laurentian Great Lakes to potentially find strategies to reduce the extent and severity of future eutrophication.

Predicted avian responses to bioenergy development scenarios in an intensive agricultural landscape

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Mitchell, Rob B.; McCoy, Tim D.; Guan, Qingfeng

2015-01-01

Conversion of native prairie to agriculture has increased food and bioenergy production but decreased wildlife habitat. However, enrollment of highly erodible cropland in conservation programs has compensated for some grassland loss. In the future, climate change and production of second-generation perennial biofuel crops could further transform agricultural landscapes and increase or decrease grassland area. Switchgrass (Panicum virgatum) is an alternative biofuel feedstock that may be economically and environmentally superior to maize (Zea mays) grain for ethanol production on marginally productive lands. Switchgrass could benefit farmers economically and increase grassland area, but there is uncertainty as to how conversions between rowcrops, switchgrass monocultures and conservation grasslands might occur and affect wildlife. To explore potential impacts on grassland birds, we developed four agricultural land-use change scenarios for an intensively cultivated landscape, each driven by potential future climatic changes and ensuing irrigation limitations, ethanol demand, commodity prices, and continuation of a conservation program. For each scenario, we calculated changes in area for landcover classes and predicted changes in grassland bird abundances. Overall, birds responded positively to the replacement of rowcrops with switchgrass and negatively to the conversion of conservation grasslands to switchgrass or rowcrops. Landscape context and interactions between climate, crop water use, and irrigation availability could influence future land-use, and subsequently, avian habitat quality and quantity. Switchgrass is likely to provide higher quality avian habitat than rowcrops but lower quality habitat than conservation grasslands, and therefore, may most benefit birds in heavily cultivated, irrigation dependent landscapes under warmer and drier conditions, where economic profitability may also encourage conversions to drought tolerant bioenergy feedstocks.

The U.S. Geological Survey Land Remote Sensing Program

USGS Publications Warehouse

,

2007-01-01

The fundamental goals of the U.S. Geological Survey's Land Remote Sens-ing (LRS) Program are to provide the Federal Government and the public with a primary source of remotely sensed data and applications and to be a leader in defining the future of land remote sensing, nationally and internationally. Remotely sensed data provide information that enhance the understand-ing of ecosystems and the capabilities for predicting ecosystem change. The data promote an understanding of the role of the environment and wildlife in human health issues, the requirements for disaster response, the effects of climate variability, and the availability of energy and mineral resources. Also, as land satellite systems acquire global coverage, the program coordinates a network of international receiving stations and users of the data. It is the responsibility of the program to assure that data from land imaging satellites, airborne photography, radar, and other technologies are available to the national and global science communities.

Predicting Monsoonal-Driven Stream Discharge and Sediment Yield in Himalaya Mountain Basins with Changing Climate and Deforestation

NASA Astrophysics Data System (ADS)

Neupane, R. P.; White, J. D.

2014-12-01

Short and long term effects of site water availability impacts the spectrum of management outcomes including landslide risk, hydropower generation, and sustainable agriculture in mountain systems heavily influenced by climate and land use changes. Climate change and land use may predominantly affect the hydrologic cycle of mountain basins as soil precipitation interception is affected by land cover. Using the Soil and Water Assessment Tool, we estimated stream discharge and sediment yield associated with climate and land use changes for two Himalaya basins located at eastern and western margins of Nepal that included drainages of the Tamor and Seti Rivers. Future climate change was modeled using average output of temperature and precipitation changes derived from Special Report on Emission Scenarios (B1, A1B & A2) of 16 global circulation models for 2080 as meteorological inputs into SWAT. Land use change was modeled spatially and included 1) deforestation, 2) expansion of agricultural land, and 3) increased human settlement that were produced by considering current land use with projected changes associated with viability of elevation and slope characteristics of the basins capable of supporting different land use types. We found higher annual stream discharge in all GCM-derived scenarios compared to the baseline with maximum increases of 13 and 8% in SRES-A2 and SRES-A1B for the Tamor and Seti basins, respectively. With 7% of original forest land removed, sediment yield for Tamor basin was estimated to be 65% higher, but increased to 124% for the SRES-B1 scenario. For the Seti basin, 4% deforestation yielded 33% more sediment for the SRES-A1B scenario. Our results indicated that combined effects of future, intensified monsoon rainfall with deforestation lead to dramatic potential for increased stream discharge and sediment yield as rainfall on steep slopes with thin exposed soils increases surface runoff and soil erosion in the Himalayas. This effect appears to be geographically important with higher influence in the eastern Tamor basin potentially due to longer and stronger monsoonal period of that area. Future slope stability and sediment deposition in downstream reservoirs are important future potential vulnerabilities for these basins of which land management plays an important mediating role.

76 FR 45077 - Endangered and Threatened Wildlife and Plants; Designation of Critical Habitat for Ipomopsis...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-27

... and heat waves over most land areas will likely increase (IPCC 2007, pp. 13, 53). The IPCC predicts..., future projections for the Southwest include increased temperatures; more intense and longer-lasting heat..., droughty, and deficient in nutrients. Species that occupy such sites have been called ``stress- tolerators...

Orbiter lessons learned: A guide to future vehicle development

NASA Technical Reports Server (NTRS)

Greenberg, Harry Stan

1993-01-01

Topics addressed are: (1) wind persistence loads methodology; (2) emphasize supportability in design of reusable vehicles; (3) design for robustness; (4) improved aerodynamic environment prediction methods for complex vehicles; (5) automated integration of aerothermal, manufacturing, and structures analysis; (6) continued electronic documentation of structural design and analysis; and (7) landing gear rollout load simulations.

Ohio Environmental Education Areas.

ERIC Educational Resources Information Center

Melvin, Ruth W.

This is a guide to regional sites in Ohio which can be studied in regard to resource management; land use; the quality of air, water, soil; and reclamation. The first section of the guide includes brief descriptions of Ohio's natural features at the present time, accounts of past appearances and events, and predictions for the future. In the…

Shallow aquifer response to climate change scenarios in a small catchment in the Guarani Aquifer outcrop zone.

PubMed

Melo, Davi C D; Wendland, Edson

2017-05-01

Water availability restrictions are already a reality in several countries. This issue is likely to worsen due to climate change, predicted for the upcoming decades. This study aims to estimate the impacts of climate change on groundwater system in the Guarani Aquifer outcrop zone. Global Climate Models (GCM) outputs were used as inputs to a water balance model, which produced recharge estimates for the groundwater model. Recharge was estimated across different land use types considering a control period from 2004 to 2014, and a future period from 2081 to 2099. Major changes in monthly rainfall means are expected to take place in dry seasons. Most of the analysed scenarios predict increase of more than 2 ºC in monthly mean temperatures. Comparing the control and future runs, our results showed a mean recharge change among scenarios that ranged from ~-80 to ~+60%, depending on the land use type. As a result of such decrease in recharge rates, the response given by the groundwater model indicates a lowering of the water table under most scenarios.

Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity.

PubMed

Mercado, Lina M; Medlyn, Belinda E; Huntingford, Chris; Oliver, Rebecca J; Clark, Douglas B; Sitch, Stephen; Zelazowski, Przemyslaw; Kattge, Jens; Harper, Anna B; Cox, Peter M

2018-06-01

Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO 2 . © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

The Fate of Amazonian Ecosystems over the Coming Century Arising from Changes in Climate, Atmospheric CO2 and Land-use

NASA Astrophysics Data System (ADS)

Moorcroft, P. R.; Zhang, K.; Castanho, A. D. D. A.; Galbraith, D.; Moghim, S.; Levine, N. M.; Bras, R. L.; Coe, M. T.; Costa, M. H.; Malhi, Y.; Longo, M.; Knox, R. G.; McKnight, S. L.; Wang, J.

2014-12-01

There is considerable interest and uncertainty regarding the expected fate of the Amazon over the coming century in face of the combined impacts of climate change, rising atmospheric CO2 levels, and on-going land transformation in the region. In this analysis, we explore the fate of Amazonian ecosystems under projected climate, CO2 and land-use change in the 21st century using three state-of-the-art terrestrial biosphere models (ED2, IBIS, and JULES) driven by three representative, bias-corrected GCM climate projections (PCM1, CCSM3, and HadCM3) under the SRES A2 scenario, coupled with two land-use change scenarios. We assess the relative roles of climate change, CO2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change depend strongly on the direction and severity of projected changes in precipitation regimes within the region: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%; however, the models predict that CO2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and as a result sustain high biomass forests, even under the driest climate scenario. Land-use change and changes in fire frequency are predicted cause additional aboveground live biomass loss and changes in forest extent. The relative impact of land-use and fire dynamics versus the impacts of climate and CO2 on the Amazon varies considerably, depending on both the climate and land-use scenarios used and on the terrestrial biosphere model, highlighting the importance of improved understanding of all four factors -- future climate, CO2 fertilization effects, fire and land-use -- to the fate of the Amazon over the coming century.

Modelling soil erosion at European scale: the importance of management practices and the future climate and land use scenarios

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Poesen, Jean; Lugato, Emanuele; Montanarella, Luca; Alewell, Christine; Borrelli, Pasquale

2017-04-01

The implementation of RUSLE2015 for modelling soil loss by water erosion at European scale has introduced important aspects related to management practices. The policy measurements such as reduced tillage, crop residues, cover crops, grass margins, stone walls and contouring have been incorporated in the RUSLE2015 modelling platform. The recent policy interventions introduced in Good Agricultural Environmental Conditions of Common Agricultural Policy have reduced the rate of soil loss in the EU by an average of 9.5% overall, and by 20% for arable lands (NATURE, 526, 195). However, further economic and political action should rebrand the value of soil as part of ecosystem services, increase the income of rural land owners, involve young farmers and organize regional services for licensing land use changes (Land Degradation and Development, 27 (6): 1547-1551). RUSLE2015 is combining the future policy scenarios and land use changes introduced by predictions of LUISA Territorial Modelling Platform. Latest developments in RUSLE2015 allow also incorporating the climate change scenarios and the forthcoming intensification of rainfall in North and Central Europe contrary to mixed trends in Mediterranean basin. The rainfall erosivity predictions estimate a mean increase by 18% in European Union by 2050. Recently, a module of CENTURY model was coupled with the RUSLE2015 for estimating the effect of erosion in current carbon balance in European agricultural lands (Global Change Biology, 22(5), 1976-1984; 2016). Finally, the monthly erosivity datasets (Science of the Total Environment, 579: 1298-1315) introduce a dynamic component in RUSLE2015 and it is a step towards spatio-temporal soil erosion mapping at continental scale. The monthly mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should apply in different seasons of the year. In the future, the soil erosion-modelling platform will incorporate the land use intra-annual variability, sediment transport and economic assessments of land degradation. Panagos, P., Borrelli, P., Robinson, D.A. 2015. Common Agricultural Policy: Tackling soil loss across Europe. Nature 526: 195 Panagos, P., Imeson, A., Meusburger, K., Borrelli, P., Poesen, J., Alewell, C. 2016. Soil Conservation in Europe: Wish or Reality? Land Degradation and Development, 27(6): 1547-1551 Lugato, E., Paustian, K., Panagos, P. et al. 2016. Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution. Global Change Biology. 22(5): 1976-1984 Ballabio, C., Borrelli, P. et al. 2017. Mapping monthly rainfall erosivity in Europe. Science of the Total Environment, 579: 1298-1315

Forward and backward evolution of the Calhoun CZO: the effect of natural and anthropogenic disturbances

NASA Astrophysics Data System (ADS)

Bonetti, S.; Porporato, A. M.

2017-12-01

The time evolution of a landscape topography through erosional and depositional mechanisms is modified by both human and natural disturbances. This is particularly evident in the Calhoun Critical Zone Observatory, where decades of land-use resulted in a distinct topography with gullies, interfluves, hillslopes and significantly eroded areas. Understanding the role of different geomorphological processes that led to these conditions is crucial to reconstruct sediment and soil carbon fluxes, predict critical conditions of landscape degradation, and implement strategies of land recovery. To model these dynamics, an analytical theory of the drainage area (which represents a surrogate for water surface runoff responsible for fluvial incision) is used to evolve ridge and valley lines. Furthermore, the coupled dynamics of surface water runoff and landscape evolution is analyzed theoretically and numerically to detect thresholds leading to either stable landscape configurations or critical conditions of land erosion. Observed erosional cycles due to vegetation disturbances are explored and used to predict future evolutions under various levels of anthropogenic disturbance.

Modelling the Impacts of Changing Land Cover/Land Use and Climate on Flooding in the Elk River Watershed, British Columbia

NASA Astrophysics Data System (ADS)

Barnes, C. C.; Byrne, J. M.; Hopkinson, C.; MacDonald, R. J.; Johnson, D. L.

2015-12-01

The Elk River is a mountain watershed located along the eastern border of British Columbia, Canada. The Elk River is confined by railway bridges, roads, and urban areas. Flooding has been a concern in the valley for more than a century. The most recent major flood event occurred in 2013 affecting several communities. River modifications such as riprapped dykes, channelization, and dredging have occurred in an attempt to reduce inundation, with limited success. Significant changes in land cover/land use (LCLU) such as natural state to urban, forestry practices, and mining from underground to mountaintop/valley fill have changed terrain and ground surfaces thereby altering water infiltration and runoff processes in the watershed. Future climate change in this region is expected to alter air temperature and precipitation as well as produce an earlier seasonal spring freshet potentially impacting future flood events. The objective of this research is to model historical and future hydrological conditions to identify flood frequency and risk under a range of climate and LCLU change scenarios in the Elk River watershed. Historic remote sensing data, forest management plans, and mining industry production/post-mining reclamation plans will be used to create a predictive past and future LCLU time series. A range of future air temperature and precipitation scenarios will be developed based on accepted Global Climate Modelling (GCM) research to examine how the hydrometeorological conditions may be altered under a range of future climate scenarios. The GENESYS (GENerate Earth SYstems Science input) hydrometeorological model will be used to simulate climate and LCLU to assess historic and potential future flood frequency and magnitude. Results will be used to create innovative flood mitigation, adaptation, and management strategies for the Elk River with the intent of being wildlife friendly and non-destructive to ecosystems and habitats for native species.

The dynamic and indirect spatial effects of neighborhood conditions on land value, spatial panel dynamic econometrics model

NASA Astrophysics Data System (ADS)

Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

2017-05-01

Land value is the product of past decision of its use leading to its value, as well as the value of the surrounded land. It is also affected by the local characteristic and the spillover development demand of the previous time period. The effect of each factor on land value will have dynamic and spatial virtues. Thus, a spatial panel dynamic model is used to estimate the particular effects. The model will be useful for predicting the future land value or the effect of implemented policy on land value. The objective of this paper is to derive the dynamic and indirect spatial marginal effects of the land characteristic and the spillover development demand on land value. Each effect is the partial derivative of the expected land value based on the spatial dynamic model with respect to each variable, by considering different time period and different location. The results indicate that the instant change of local or neighborhood characteristics on land value affect the local and the immediate neighborhood land value. However, the longer the change take place, the effect will spread further, not only on the immediate neighborhood.

Modelling and analyzing the watershed dynamics using Cellular Automata (CA)-Markov model - A geo-information based approach

NASA Astrophysics Data System (ADS)

Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.

2012-08-01

Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions

PubMed Central

Hovick, Torre J.; Dahlgren, David K.; Papeş, Monica; Elmore, R. Dwayne; Pitman, James C.

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003–2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern. PMID:26317349

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

PubMed

Hovick, Torre J; Dahlgren, David K; Papeş, Monica; Elmore, R Dwayne; Pitman, James C

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003-2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Yu, Y.; Liu, L.

2015-12-01

Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

Future battlegrounds for conservation under global change

PubMed Central

Lee, Tien Ming; Jetz, Walter

2008-01-01

Global biodiversity is under significant threat from the combined effects of human-induced climate and land-use change. Covering 12% of the Earth's terrestrial surface, protected areas are crucial for conserving biodiversity and supporting ecological processes beneficial to human well-being, but their selection and design are usually uninformed about future global change. Here, we quantify the exposure of the global reserve network to projected climate and land-use change according to the Millennium Ecosystem Assessment and set these threats in relation to the conservation value and capacity of biogeographic and geopolitical regions. We find that geographical patterns of past human impact on the land cover only poorly predict those of forecasted change, thus revealing the inadequacy of existing global conservation prioritization templates. Projected conservation risk, measured as regional levels of land-cover change in relation to area protected, is the greatest at high latitudes (due to climate change) and tropics/subtropics (due to land-use change). Only some high-latitude nations prone to high conservation risk are also of high conservation value, but their high relative wealth may facilitate additional conservation efforts. In contrast, most low-latitude nations tend to be of high conservation value, but they often have limited capacity for conservation which may exacerbate the global biodiversity extinction crisis. While our approach will clearly benefit from improved land-cover projections and a thorough understanding of how species range will shift under climate change, our results provide a first global quantitative demonstration of the urgent need to consider future environmental change in reserve-based conservation planning. They further highlight the pressing need for new reserves in target regions and support a much extended ‘north–south’ transfer of conservation resources that maximizes biodiversity conservation while mitigating global climate change. PMID:18302999

Development of European NO2 Land Use Regression Model for present and future exposure assessment: Implications for policy analysis.

PubMed

Vizcaino, Pilar; Lavalle, Carlo

2018-05-04

A new Land Use Regression model was built to develop pan-European 100 m resolution maps of NO 2 concentrations. The model was built using NO 2 concentrations from routine monitoring stations available in the Airbase database as dependent variable. Predictor variables included land use, road traffic proxies, population density, climatic and topographical variables, and distance to sea. In order to capture international and inter regional disparities not accounted for with the mentioned predictor variables, additional proxies of NO 2 concentrations, like levels of activity intensity and NO x emissions for specific sectors, were also included. The model was built using Random Forest techniques. Model performance was relatively good given the EU-wide scale (R 2  = 0.53). Output predictions of annual average concentrations of NO 2 were in line with other existing models in terms of spatial distribution and values of concentration. The model was validated for year 2015, comparing model predictions derived from updated values of independent variables, with concentrations in monitoring stations for that year. The algorithm was then used to model future concentrations up to the year 2030, considering different emission scenarios as well as changes in land use, population distribution and economic factors assuming the most likely socio-economic trends. Levels of exposure were derived from maps of concentration. The model proved to be a useful tool for the ex-ante evaluation of specific air pollution mitigation measures, and more broadly, for impact assessment of EU policies on territorial development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Wetland features and landscape context predict the risk of wetland habitat loss.

PubMed

Gutzwiller, Kevin J; Flather, Curtis H

2011-04-01

Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive regression splines to develop a model to predict the risk of wetland habitat loss as a function of wetland features and landscape context. Fates of wetland habitats from 1992 to 1997 were obtained from the National Resources Inventory for the U.S. Forest Service's Southern Region, and land-cover data were obtained from the National Land Cover Data. We randomly selected 70% of our 40 617 observations to build the model (n = 28 432), and randomly divided the remaining 30% of the data into five Test data sets (n = 2437 each). The wetland and landscape variables that were important in the model, and their relative contributions to the model's predictive ability (100 = largest, 0 = smallest), were land-cover/ land-use of the surrounding landscape (100.0), size and proximity of development patches within 570 m (39.5), land ownership (39.1), road density within 570 m (37.5), percent woody and herbaceous wetland cover within 570 m (27.8), size and proximity of development patches within 5130 m (25.7), percent grasslands/herbaceous plants and pasture/hay cover within 5130 m (21.7), wetland type (21.2), and percent woody and herbaceous wetland cover within 1710 m (16.6). For the five Test data sets, Kappa statistics (0.40, 0.50, 0.52, 0.55, 0.56; P < 0.0001), area-under-the-receiver-operating-curve (AUC) statistics (0.78, 0.82, 0.83, 0.83, 0.84; P < 0.0001), and percent correct prediction of wetland habitat loss (69.1, 80.4, 81.7, 82.3, 83.1) indicated the model generally had substantial predictive ability across the South. Policy analysts and land-use planners can use the model and associated maps to prioritize at-risk wetlands for protection, evaluate wetland habitat connectivity, predict future conversion of wetland habitat based on projected land-use trends, and assess the effectiveness of wetland conservation programs.

Projecting optimal land-use and -management strategies under population growth and climate change using a coupled ecosystem & land use model framework

NASA Astrophysics Data System (ADS)

Rabin, Sam; Alexander, Peter; Anthoni, Peter; Henry, Roslyn; Huntingford, Chris; Pugh, Thomas; Rounsevell, Mark; Arneth, Almut

2017-04-01

A major question facing humanity is how well agricultural production systems will be able to feed the world in a future of rapid climate change, population growth, and demand shifts—all while minimizing our impact on the natural world. Global modeling has frequently been used to investigate certain aspects of this question, but in order to properly address the challenge, no one part of the human-environmental system can be assessed in isolation. It is especially critical that the effect on agricultural yields of changing temperature and precipitation regimes (including seasonal timing and frequency and intensity of extreme events), as well as rising atmospheric carbon dioxide levels, be taken into account when planning for future food security. Coupled modeling efforts, where changes in various parts of the Earth system are allowed to feed back onto one another, represent a powerful strategy in this regard. This presentation describes the structure and initial results of an effort to couple a biologically-representative vegetation and crop production simulator, LPJ-GUESS, with the climate emulator IMOGEN and the land-use model PLUMv2. With IMOGEN providing detailed future weather simulations, LPJ-GUESS simulates natural vegetation as well as cropland and pasture/rangeland; the simulated exchange of greenhouse gases between the land and atmosphere feeds back into IMOGEN's predictions. LPJ-GUESS also produces potential vegetation yields for irrigated vs. rainfed crops under three levels of nitrogen fertilizer addition. PLUMv2 combines these potential yields with endogenous demand and agricultural commodity price to calculate an optimal set of land use distributions and management strategies across the world for the next five years of simulation, based on socio-economic scenario data. These land uses are then fed back into LPJ-GUESS, and the cycle of climate, greenhouse gas emissions, crop yields, and land-use change continues. The globally gridded nature of the model—at 0.5-degree resolution across the world—generates spatially explicit projections at a sub-national scale relevant to individual land managers. Here, we present the results of using the LPJ-GUESS-PLUM-IMOGEN coupled model to project agricultural production and management strategies under several scenarios of greenhouse gas emissions (the Representative Concentration Pathways) and socioeconomic futures (the Shared Socioeconomic Pathways) through the year 2100. In the future, the coupled model could be used to generate projections for alternative scenarios: for example, to consider the implications from land-based climate change mitigation policies, or changes to international trade tariffs regimes.

Large-Scale Controls and Characteristics of Fire Activity in Central Chile, 2001-2015

NASA Astrophysics Data System (ADS)

McWethy, D. B.; Pauchard, A.; García, R.; Holz, A.; González, M.; Veblen, T. T.; Stahl, J.

2016-12-01

In recent decades, fire activity has increased in many ecosystems worldwide, even where fuel conditions and natural ignitions historically limited fire activity, and this increase begs questions of whether climate change, land-use change, and/or altered vegetation are responsible. Increased frequency of large fires in these settings has been attributed to drier-than-average summers and longer fire seasons as well as fuel accumulation related to ENSO events, raising concerns about the trajectory of post-fire vegetation dynamics and future fire regimes. In temperate and Mediterranean forests of central Chile, recent large fires associated with altered ecosystems, climate variability and land-use change highlight the risk and hazard of increasing fire activity yet the causes and consequences are poorly understood. To better understand characteristics of recent fire activity, key drivers of fire occurrence and the spatial probability of wildfire we examined the relationship between fire activity derived from MODIS satellite imagery and biophysical, land-cover and land-use variables. The probability of fire occurrence and annual area burned was best predicted by seasonal precipitation, annual temperature and land cover type. The likelihood of fire occurrence was greatest in Matorral shrublands, agricultural lands (including pasture lands) and Pinus and Eucalyptus plantations, highlighting the importance of vegetation type and fuel flammability as a critical control on fire activity. Our results suggest that land-use change responsible for the widespread presence of highly flammable vegetation and projections for continued warming and drying will likely combine to promote the occurrence of large fires in central Chile in the future.

A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

NASA Astrophysics Data System (ADS)

Gronewold, A.; Alameddine, I.; Anderson, R. M.

2009-12-01

Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, as well as those addressing coastal population dynamics and sea level rise. Our approach has several advantages, including the propagation of parameter uncertainty through a nonparametric probability distribution which avoids common pitfalls of fitting parameters and model error structure to a predetermined parametric distribution function. In addition, by explicitly acknowledging correlation between model parameters (and reflecting those correlations in our predictive model) our model yields relatively efficient prediction intervals (unlike those in the current literature which are often unnecessarily large, and may lead to overly-conservative management actions). Finally, our model helps improve understanding of the rainfall-runoff process by identifying model parameters (and associated catchment attributes) which are most sensitive to current and future land use change patterns. Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

Initializing carbon cycle predictions from the Community Land Model by assimilating global biomass observations

NASA Astrophysics Data System (ADS)

Fox, A. M.; Hoar, T. J.; Smith, W. K.; Moore, D. J.

2017-12-01

The locations and longevity of terrestrial carbon sinks remain uncertain, however it is clear that in order to predict long-term climate changes the role of the biosphere in surface energy and carbon balance must be understood and incorporated into earth system models (ESMs). Aboveground biomass, the amount of carbon stored in vegetation, is a key component of the terrestrial carbon cycle, representing the balance of uptake through gross primary productivity (GPP), losses from respiration, senescence and mortality over hundreds of years. The best predictions of current and future land-atmosphere fluxes are likely from the integration of process-based knowledge contained in models and information from observations of changes in carbon stocks using data assimilation (DA). By exploiting long times series, it is possible to accurately detect variability and change in carbon cycle dynamics through monitoring ecosystem states, for example biomass derived from vegetation optical depth (VOD), and use this information to initialize models before making predictions. To make maximum use of information about the current state of global ecosystems when using models we have developed a system that combines the Community Land Model (CLM) with the Data Assimilation Research Testbed (DART), a community tool for ensemble DA. This DA system is highly innovative in its complexity, completeness and capabilities. Here we described a series of activities, using both Observation System Simulation Experiments (OSSEs) and real observations, that have allowed us to quantify the potential impact of assimilating VOD data into CLM-DART on future land-atmosphere fluxes. VOD data are particularly suitable to use in this activity due to their long temporal coverage and appropriate scale when combined with CLM, but their absolute values rely on many assumptions. Therefore, we have had to assess the implications of the VOD retrieval algorithms, with an emphasis on detecting uncertainty due to assumptions and inputs in the algorithms that are incompatible with those encoded within CLM. It is probable that VOD describes changes in biomass more accurately than absolute values, so in additional to sequential assimilation of observations, we have tested alternative filter algorithms, and assimilating VOD anomalies.

Current & future vulnerability of sarasota county Florida to hurricane storm surge & sea level rise

USGS Publications Warehouse

Frazier, T.; Wood, N.; Yarnal, B.

2008-01-01

Coastal communities in portions of the United States are vulnerable to storm-surge inundation from hurricanes and this vulnerability will likely increase, given predicted rises in sea level from climate change and growing coastal development. In this paper, we provide an overview of research to determine current and future societal vulnerability to hurricane storm-surge inundation and to help public officials and planners integrate these scenarios into their long-range land use plans. Our case study is Sarasota County, Florida, where planners face the challenge of balancing increasing population growth and development with the desire to lower vulnerability to storm surge. Initial results indicate that a large proportion of Sarasota County's residential and employee populations are in areas prone to storm-surge inundation from a Category 5 hurricane. This hazard zone increases when accounting for potential sea-level-rise scenarios, thereby putting additional populations at risk. Subsequent project phases involve the development of future land use and vulnerability scenarios in collaboration with local officials. Copyright ASCE 2008.

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

NASA Technical Reports Server (NTRS)

Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

2010-01-01

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

The importance of considering shifts in seasonal changes in discharges when prediciting future phosphorus loads in streams

USDA-ARS?s Scientific Manuscript database

In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses t...

Back to the future: assessing accuracy and sensitivity of a forest growth model

Treesearch

Susan Hummel; Paul Meznarich

2014-01-01

The Forest Vegetation Simulator (FVS) is a widely used computer model that projects forest growth and predicts the effects of disturbances such as fire, insects, harvests, or disease. Land managers often use these projections to decide among silvicultural options and estimate the potential effects of these options on forest conditions. Despite FVS's popularity,...

Medium density fiberboards from plantation grown Eucalyptus saligna

Treesearch

Andrzej Krzysik; John A. Youngquist; James H. Muehl; Fabio Spina Franca

1999-01-01

The production of industrial wood from natural forests is predicted to decline in the future. Factors that will contribute to this decline include changes in land use patterns, depletion of resources in some parts of the world, and the withdrawal of forest areas from industrial production in order to provide for environmental, recreational, and other social needs....

Proceedings of the Redwood Region Forest Science Symposium: What does the future hold?

Treesearch

Richard B. Standiford; Gregory A. Giusti; Yana Valachovic; William J. Zielinski; Michael J. Furniss

2007-01-01

Policies and strategies that guide use and management of lands in the coastal ecoregion are dependent on objective scientific information. In recent years attention to this region has increased. Correspondingly, there has been much new information collected. Efforts such as the Caspar Creek Watershed Conference and the Scientific Basis for the Prediction of Cumulative...

Representing northern peatland microtopography and hydrology within the Community Land Model

Treesearch

X. Shi; P.E. Thornton; D.M. Ricciuto; P J. Hanson; J. Mao; Stephen Sebestyen; N.A. Griffiths; G. Bisht

2015-01-01

Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth...

Evaluating the ecological sustainability of a pinyon-juniper grassland ecosystem in northern Arizona

Treesearch

Reuben Weisz; Jack Triepke; Don Vandendriesche; Mike Manthei; Jim Youtz; Jerry Simon; Wayne Robbie

2010-01-01

In order to develop strategic land management plans, managers must assess current and future ecological conditions. Climate change has expanded the need to assess the sustainability of ecosystems and predict their conditions under different climate change and management scenarios using landscape dynamics simulation models. We present a methodology for developing a...

Impacts of rural development on Yellowstone wildlife: linking grizzly bear Ursus arctos demographics with projected residential growth

USGS Publications Warehouse

Schwartz, Charles C.; Gude, Patricia H.; Landenburger, Lisa; Haroldson, Mark A.; Podruzny, Shannon

2012-01-01

Exurban development is consuming wildlife habitat within the Greater Yellowstone Ecosystem with potential consequences to the long-term conservation of grizzly bears Ursus arctos. We assessed the impacts of alternative future land-use scenarios by linking an existing regression-based simulation model predicting rural development with a spatially explicit model that predicted bear survival. Using demographic criteria that predict population trajectory, we portioned habitats into either source or sink, and projected the loss of source habitat associated with four different build out (new home construction) scenarios through 2020. Under boom growth, we predicted that 12 km2 of source habitat were converted to sink habitat within the Grizzly Bear Recovery Zone (RZ), 189 km2 were converted within the current distribution of grizzly bears outside of the RZ, and 289 km2 were converted in the area outside the RZ identified as suitable grizzly bear habitat. Our findings showed that extremely low densities of residential development created sink habitats. We suggest that tools, such as those outlined in this article, in addition to zoning and subdivision regulation may prove more practical, and the most effective means of retaining large areas of undeveloped land and conserving grizzly bear source habitat will likely require a landscape-scale approach. We recommend a focus on land conservation efforts that retain open space (easements, purchases and trades) coupled with the implementation of ‘bear community programmes’ on an ecosystem wide basis in an effort to minimize human-bear conflicts, minimize management-related bear mortalities associated with preventable conflicts and to safeguard human communities. Our approach has application to other species and areas, and it has illustrated how spatially explicit demographic models can be combined with models predicting land-use change to help focus conservation priorities.

Simulating the effect of land use and climate change on upland soil carbon stock of Wales using ECOSSE

NASA Astrophysics Data System (ADS)

Rani Nayak, Dali; Gottschalk, Pia; Evans, Chris; Smith, Pete; Smith, Jo

2010-05-01

Within Wales soils hold between 400-500 MtC, over half of this carbon is stored in organic and organo-mineral soil which cover less than 20% of the land area of Wales. It has been predicted that climate change will increasingly have an impact on the C stock of soils in Wales. Higher temperatures will increase the rate of decomposition of organic matter, leading to increased C losses. However increased net primary production (NPP), leading to increased inputs of organic matter, may offset this. Land use plays a major role in determining the level of soil C and the direction of change in status (soil as a source or sink). We present here an assessment of the effect of land use change and climate change on the upland soil carbon stock of Wales in 3 different catchments i.e. Migneint, Plynlimon and Pontbren using a process-based model of soil carbon and nitrogen dynamics, ECOSSE. The uncertainties introduced in the simulations by using only the data available at national scale are determined. The ECOSSE model (1,2) has been developed to simulate greenhouse gas emissions from both organic and mineral soils. ECOSSE was derived from RothC (3) and SUNDIAL (4,5) and predicts the impacts of changes in land use and climate on emissions and soil carbon stock. Simulated changes in soil C are dependent on the type of land use change, the soil type where the land use change is occurring, and the C content of soil under the initial and final land uses. At Migneint and Plynlimon, the major part of the losses occurs due to the conversion of semi-natural land to grassland. Reducing the land use change from semi-natural to grassland is the main measure needed to mitigate losses of soil C. At Pontbren, the model predicts a net gain in soil C with the predicted land use change, so there is no need to mitigate. Simulations of future changes in soil C to 2050 showed very small changes in soil C due to climate compared to changes due to land use change. At the selected catchments, changes in soil C due to the impacts of land use change were predicted to be up to 1000 times greater than the changes predicted due to climate change. This is encouraging, as it illustrates the great potential for C losses due to climate change to be mitigated by changing land use. 1. Smith P, et al 2007. SEERAD Report. ISBN 978 0 7559 1498 2. 166pp. 2. Smith JU, et al 2009. RERAD Report. In press. 3. Coleman K & Jenkinson DS 1996. In: Evaluation of Soil Organic Matter Models Using Existing, Long-Term Datasets, NATO ASI Series I, Vol.38 (eds Powlson DS, Smith P, Smith JU), pp. 237-246. Springer-Verlag, Heidelberg, Germany. 4. Bradbury NJ, et al 1993. Journal of Agricultural Science, Cambridge 121, 363-379. 5. Smith JU, et al 1996. Agronomy Journal 88, 38-42.

Impacts of climate change and renewable energy development on habitat of an endemic squirrel, Xerospermophilus mohavensis, in the Mojave Desert, USA

USGS Publications Warehouse

Inman, Richard D.; Esque, Todd C.; Nussear, Kenneth E.; Leitner, Philip; Matocq, Marjorie D.; Weisberg, Peter J.; Dilts, Thomas E.

2016-01-01

Predicting changes in species distributions under a changing climate is becoming widespread with the use of species distribution models (SDMs). The resulting predictions of future potential habitat can be cast in light of planned land use changes, such as urban expansion and energy development to identify areas with potential conflict. However, SDMs rarely incorporate an understanding of dispersal capacity, and therefore assume unlimited dispersal in potential range shifts under uncertain climate futures. We use SDMs to predict future distributions of the Mojave ground squirrel, Xerospermophilus mohavensis Merriam, and incorporate partial dispersal models informed by field data on juvenile dispersal to assess projected impact of climate change and energy development on future distributions of X. mohavensis. Our models predict loss of extant habitat, but also concurrent gains of new habitat under two scenarios of future climate change. Under the B1 emissions scenario- a storyline describing a convergent world with emphasis on curbing greenhouse gas emissions- our models predicted losses of up to 64% of extant habitat by 2080, while under the increased greenhouse gas emissions of the A2 scenario, we suggest losses of 56%. New potential habitat may become available to X. mohavensis, thereby offsetting as much as 6330 km2 (50%) of the current habitat lost. Habitat lost due to planned energy development was marginal compared to habitat lost from changing climates, but disproportionately affected current habitat. Future areas of overlap in potential habitat between the two climate change scenarios are identified and discussed in context of proposed energy development.

Problems of land reclamation during liquidation of coalmining enterprises

NASA Astrophysics Data System (ADS)

Pospehov, G. B.; Pankratova, K. V.; Straupnik, I. A.; Ustiugov, D. L.

2017-10-01

The paper presents data on the influence of coal-mining industry elimination on the deformation of land surface which can cause accidents and destructions of buildings and constructions located nearby the closed pits or mines. The analysis is carried out and the major factors which influence change of the intense deformed condition of the massif of rocks were revealed. The example of the monitoring system which will provide researchers with information for preparation of the project of a pit or a mine closing is presented, and it also will allow one to predict behavior of the massif in the future.

Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.; Sharp, Leigh Anne; McGinnis, Tommy S.; Wood, Bernard; Piazza, Sarai

2018-01-01

The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana, vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

A regional neural network model for predicting mean daily river water temperature

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

JPL's Role in Advancing Earth System Science to Meet the Challenges of Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2012-01-01

Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Optimal stomatal behaviour around the world

DOE PAGES

Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; ...

2015-03-02

Stomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs accordingmore » to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model 1 and the leaf and wood economics spectrum 2,3. We also demonstrate a global relationship with climate. In conclusion, these findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.« less

Climate and land use changes effects on soil organic carbon stocks in a Mediterranean semi-natural area.

PubMed

Lozano-García, Beatriz; Muñoz-Rojas, Miriam; Parras-Alcántara, Luis

2017-02-01

A thorough knowledge of the effects of climate and land use changes on the soil carbon pool is critical to planning effective strategies for adaptation and mitigation in future scenarios of global climate and land use change. In this study, we used CarboSOIL model to predict changes in soil organic carbon stocks in a semi-natural area of Southern Spain in three different time horizons (2040, 2070, 2100), considering two general circulation models (BCM2 and ECHAM5) and three IPCC scenarios (A1b, A2, B2). The effects of potential land use changes from natural vegetation (Mediterranean evergreen oak woodland) to agricultural land (olive grove and cereal) on soil organic carbon stocks were also evaluated. Predicted values of SOC contents correlated well those measured (R2 ranging from 0.71 at 0-25cm to 0.97 at 50-75cm) showing the efficiency of the model. Results showed substantial differences among time horizons, climate and land use scenarios and soil depth with larger decreases of soil organic carbon stocks in the long term (2100 time horizon) and particularly in olive groves. The combination of climate and land use scenarios (in particular conversion from current 'dehesa' to olive groves) resulted in yet higher losses of soil organic carbon stocks, e.g. -30, -15 and -33% in the 0-25, 25-50 and 50-75cm sections respectively. This study shows the importance of soil organic carbon stocks assessment under both climate and land use scenarios at different soil sections and point towards possible directions for appropriate land use management in Mediterranean semi natural areas. Copyright © 2016 Elsevier B.V. All rights reserved.

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

NASA Technical Reports Server (NTRS)

Laurance, William F.

2004-01-01

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Quantifying and predicting historical and future patterns of carbon fluxes from the North American Continent to Ocean

NASA Astrophysics Data System (ADS)

Tian, H.; Zhang, B.; Xu, R.; Yang, J.; Yao, Y.; Pan, S.; Lohrenz, S. E.; Cai, W. J.; He, R.; Najjar, R. G.; Friedrichs, M. A. M.; Hofmann, E. E.

2017-12-01

Carbon export through river channels to coastal waters is a fundamental component of the global carbon cycle. Changes in the terrestrial environment, both natural (e.g., climatic change, enriched CO2 concentration, and elevated ozone concentration) and anthropogenic (e.g, deforestation, cropland expansion, and urbanization) have greatly altered carbon production, stocks, decomposition, movement and export from land to river and ocean systems. However, the magnitude and spatiotemporal patterns of lateral carbon fluxes from land to oceans and the underlying mechanisms responsible for these fluxes remain far from certain. Here we applied a process-based land model with explicit representation of carbon processes in stream and rivers (Dynamic Land Ecosystem Model: DLEM 2.0) to examine how changes in climate, land use, atmospheric CO2, and nitrogen deposition have affected the carbon fluxes from North American continent to Ocean during 1980-2015. Our simulated results indicated that terrestrial carbon export shows substantially spatial and temporal variability. Of the five sub-regions (Arctic coast, Pacific coast, Gulf of Mexico, Atlantic coast, and Great lakes), the Arctic sub-region provides the highest DOC flux, whereas the Gulf of Mexico sub-region provided the highest DIC flux. However, terrestrial carbon export to the arctic oceans showed increasing trends for both DOC and DIC, whereas DOC and DIC export to the Gulf of Mexico decreased in the recent decades. Future pattern of riverine carbon fluxes would be largely dependent on the climate change and land use scenarios.

An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

NASA Astrophysics Data System (ADS)

Moulds, S.; Buytaert, W.; Mijic, A.

2015-04-01

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

Characterizing the landscape dynamics of an invasive plant and risk of invasion using remote sensing.

PubMed

Bradley, Bethany A; Mustard, John F

2006-06-01

Improved understanding of the spatial dynamics of invasive plant species may lead to more effective land management and reduced future invasion. Here, we identified the spatial extents of nonnative cheatgrass (Bromus tectorum) in the north central Great Basin using remotely sensed data from Landsat MSS, TM, and ETM+. We compared cheatgrass extents in 1973 and 2001 to six spatially explicit landscape variables: elevation, aspect, hydrographic channels, cultivation, roads, and power lines. In 2001, Cheatgrass was 10% more likely to be found in elevation ranges from 1400 to 1700 m (although the data suggest a preferential invasion into lower elevations by 2001), 6% more likely on west and northwest facing slopes, and 3% more likely within hydrographic channels. Over this time period, cheatgrass expansion was also closely linked to proximity to land use. In 2001, cheatgrass was 20% more likely to be found within 3 km of cultivation, 13% more likely to be found within 700 m of a road, and 15% more likely to be found within 1 km of a power line. Finally, in 2001 cheatgrass was 26% more likely to be present within 150 m of areas occupied by cheatgrass in 1973. Using these relationships, we created a risk map of future cheatgrass invasion that may aid land management. These results highlight the importance of including land use variables and the extents of current plant invasion in predictions of future risk.

Dryland photoautotrophic soil surface communities endangered by global change

USGS Publications Warehouse

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-01-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Dryland photoautotrophic soil surface communities endangered by global change

NASA Astrophysics Data System (ADS)

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-03-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

On-line range prediction system, part 2

NASA Technical Reports Server (NTRS)

Levan, Nhan

1988-01-01

The on-line range prediction system is designed for providing a prediction of the target range in the case of a laser data dropout. It consists of real time implementation of a Kalman filter on an IBM PC/AT equipped with necessary hardware. The system was set up and tested at Crows Landing in the Fall of 1987. The improvements made on the on-line range prediction system during 1988 are examined. Solutions are proposed and discussed to the several problems encountered during system tests. Then, the improvements made on the filter software are explained, namely, accounting for the time lag and providing data continously. Finally, the ideas are mentioned that can be considered in the future.

Continental-Scale Estimates of Runoff Using Future Climate ...

EPA Pesticide Factsheets

Recent runoff events have had serious repercussions to both natural ecosystems and human infrastructure. Understanding how shifts in storm event intensities are expected to change runoff responses are valuable for local, regional, and landscape planning. To address this challenge, relative changes in runoff using predicted future climate conditions were estimated over different biophysical areas for the CONterminous U.S. (CONUS). Runoff was estimated using the Curve Number (CN) developed by the USDA Soil Conservation Service (USDA, 1986). A seamless gridded dataset representing a CN for existing land use/land cover (LULC) across the CONUS was used along with two different storm event grids created specifically for this effort. The two storm event grids represent a 2- and a 100-year, 24-hour storm event under current climate conditions. The storm event grids were generated using a compilation of county-scale Texas USGS Intensity-Duration-Frequency (IDF) data (provided by William Asquith, USGS, Lubbock, Texas), and NOAA Atlas-2 and NOAA Atlas-14 gridded data sets. Future CN runoff was predicted using extreme storm events grids created using a method based on Kao and Ganguly (2011) where precipitation extremes reflect changes in saturated water vapor pressure of the atmosphere in response to temperature changes. The Clausius-Clapeyron relationship establishes that the total water vapor mass of fully saturated air increases with increasing temperature, leading to

Climate change impact on soil erosion in the Mandakini River Basin, North India

NASA Astrophysics Data System (ADS)

Khare, Deepak; Mondal, Arun; Kundu, Sananda; Mishra, Prabhash Kumar

2017-09-01

Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.

The future of satellite remote sensing: A worldwide assessment and prediction

NASA Technical Reports Server (NTRS)

Spann, G. W.

1984-01-01

A frame-work in which to assess and predict the future prospects for satellite remote sensing markets is provided. The scope of the analysis is the satellite-related market for data, equipment, and services. It encompasses both domestic and international markets and contains an examination of the various market characteristics by market segment (e.g., Federal Government, State and Local Governments, Academic Organizations, Industrial Companies, and Individuals) and primary applications areas (e.g., Geology, Forestry, Land Resource Management, Agriculture and Cartography). The forecasts are derived from an analysis of both U.S. and foreign market data. The evolution and current status of U.S. and Foreign markets to arrive at market growth rates is evaluated. Circumstances and events which are likely to affect the future market development are examined. A market growth scenario is presented that is consistent with past data sales trends and takes into account the dynamic nature of the future satellite remote sensing market. Several areas of current and future business opportunities available in this market are discussed. Specific worldwide forecasts are presented in three market sectors for the period 1980 to 1990.

Big changes in cold places: the future of wildlife habitat in northwest Alaska

Treesearch

Natasha Vizcarra; Bruce Marcot

2016-01-01

Higher global temperatures are changing ecosystems in the Arctic. They are becoming greener as the climate and land become more hospitable to taller vegetation. Scientists predict that woody vegetation in the Arctic will increase by more than 50 percent, and half of all vegetated areas will shift to types more suited to the higher temperatures and changing physical...

Multi-decadal trends in global terrestrial evapotranspiration and its components.

PubMed

Zhang, Yongqiang; Peña-Arancibia, Jorge L; McVicar, Tim R; Chiew, Francis H S; Vaze, Jai; Liu, Changming; Lu, Xingjie; Zheng, Hongxing; Wang, Yingping; Liu, Yi Y; Miralles, Diego G; Pan, Ming

2016-01-11

Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981-2012, and its three components: transpiration from vegetation (Et), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei). During this period, ET over land has increased significantly (p < 0.01), caused by increases in Et and Ei, which are partially counteracted by Es decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in Et over land is about twofold of the decrease in Es. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.

Multi-decadal trends in global terrestrial evapotranspiration and its components

PubMed Central

Zhang, Yongqiang; Peña-Arancibia, Jorge L.; McVicar, Tim R.; Chiew, Francis H. S.; Vaze, Jai; Liu, Changming; Lu, Xingjie; Zheng, Hongxing; Wang, Yingping; Liu, Yi Y.; Miralles, Diego G.; Pan, Ming

2016-01-01

Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (Et), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei). During this period, ET over land has increased significantly (p < 0.01), caused by increases in Et and Ei, which are partially counteracted by Es decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in Et over land is about twofold of the decrease in Es. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle. PMID:26750505

Prediction of optimal safe ground water yield and land subsidence in the Los Banos-Kettleman City area, California, using a calibrated numerical simulation model

NASA Astrophysics Data System (ADS)

Larson, K. J.; Başaǧaoǧlu, H.; Mariño, M. A.

2001-02-01

Land subsidence caused by the excessive use of ground water resources has traditionally caused serious and costly damage to the Los Banos-Kettleman City area of California's San Joaquin Valley. Although the arrival of surface water from the Central Valley Project has reduced subsidence in recent decades, the growing instability of surface water supplies has refocused attention on the future of land subsidence in the region. This paper uses integrated numerical ground water and land subsidence models to simulate land subsidence caused by ground water overdraft. The simulation model is calibrated using observed data from 1972 to 1998, and the responsiveness of the model to variations in subsidence parameters are analyzed through a sensitivity analysis. A probable future drought scenario is used to evaluate the effect on land subsidence of three management alternatives over the next thirty years. The model reveals that maintaining present practices virtually eliminates unrecoverable land subsidence, but may not be a sustainable alternative because of a growing urban population to the south and concern over the ecological implications of water exportation from the north. The two other proposed management alternatives reduce the dependency on surface water by increasing ground water withdrawal. Land subsidence is confined to tolerable levels in the more moderate of these proposals, while the more aggressive produces significant long-term subsidence. Finally, an optimization model is formulated to determine maximum ground water withdrawal from nine pumping sub-basins without causing irrecoverable subsidence during the forecast period. The optimization model reveals that withdrawal can be increased in certain areas on the eastern side of the study area without causing significant inelastic subsidence.

Effects of future climate and land use scenarios on riverine source water quality.

PubMed

Delpla, Ianis; Rodriguez, Manuel J

2014-09-15

Surface water quality is particularly sensitive to land use practices and climatic events that affect its catchment. The relative influence of a set of watershed characteristics (climate, land use, morphology and pedology) and climatic variables on two key water quality parameters (turbidity and fecal coliforms (FC)) was examined in 24 eastern Canadian catchments at various spatial scales (1 km, 5 km, 10 km and the entire catchment). A regression analysis revealed that the entire catchment was a better predictor of water quality. Based on this information, linear mixed effect models for predicting turbidity and FC levels were developed. A set of land use and climate scenarios was considered and applied within the water quality models. Four land use scenarios (no change, same rate of variation, optimistic and pessimistic) and three climate change scenarios (B1, A1B and A2) were tested and variations for the near future (2025) were assessed and compared to the reference period (2000). Climate change impacts on water quality remained low annually for this time horizon (turbidity: +1.5%, FC: +1.6%, A2 scenario). On the other hand, the influence of land use changes appeared to predominate. Significant benefits for both parameters could be expected following the optimistic scenario (turbidity: -16.4%, FC: -6.3%; p < 0.05). However, pessimistic land use scenario led to significant increases on an annual basis (turbidity: +11.6%, FC: +15.2%; p < 0.05). Additional simulations conducted for the late 21st century (2090) revealed that climate change impacts could become equivalent to those modeled for land use for this horizon. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatiotemporal patterns of evapotranspiration in response to multiple environmental factors simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoying; Mao, Jiafu; Thornton, Peter E

In this study, spatial and temporal patterns of evapotranspiration (ET) over the period of 1982-2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates derived from the FLUXNET network of eddy covariance towers using the model tree ensembles (MTE) approach. We find that climate trends and variability dominate predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, andmore » functions as the dominant factor controlling ET changes over North America, South America and Asia regions. Compared to the effect of climate change and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. For example, the aerosol deposition contribution is the third-most important factor for trends of ET over Europe, while it has the smallest impact on ET trend over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use and land cover change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Astrophysics Data System (ADS)

Golombek, M. P.

2005-05-01

Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The close correspondence between surface characteristics inferred from orbital remote sensing data and that found at the landing sites argues that future efforts to select safe landing sites will be successful. Linking the five landing sites to their remote sensing signatures suggests that they span most of the important, likely safe surfaces available for landing on Mars.

Competition for land

PubMed Central

Smith, Pete; Gregory, Peter J.; van Vuuren, Detlef; Obersteiner, Michael; Havlík, Petr; Rounsevell, Mark; Woods, Jeremy; Stehfest, Elke; Bellarby, Jessica

2010-01-01

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years. Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future. In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future. PMID:20713395

Workshop on Satellite and In situ Observations for Climate Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acker, J.G.; Busalacchi, A.

1995-02-01

Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

Workshop on Satellite and In situ Observations for Climate Prediction

NASA Technical Reports Server (NTRS)

Acker, James G.; Busalacchi, Antonio

1995-01-01

Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

Analysis of continuous GPS measurements from southern Victoria Land, Antarctica

USGS Publications Warehouse

Willis, Michael J.

2007-01-01

Several years of continuous data have been collected at remote bedrock Global Positioning System (GPS) sites in southern Victoria Land, Antarctica. Annual to sub-annual variations are observed in the position time-series. An atmospheric pressure loading (APL) effect is calculated from pressure field anomalies supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) model loading an elastic Earth model. The predicted APL signal has a moderate correlation with the vertical position time-series at McMurdo, Ross Island (International Global Navigation Satellite System Service (IGS) station MCM4), produced using a global solution. In contrast, a local solution in which MCM4 is the fiducial site generates a vertical time series for a remote site in Victoria Land (Cape Roberts, ROB4) which exhibits a low, inverse correlation with the predicted atmospheric pressure loading signal. If, in the future, known and well modeled geophysical loads can be separated from the time-series, then local hydrological loading, of interest for glaciological and climate applications, can potentially be extracted from the GPS time-series.

The Blackwater NWR inundation model. Rising sea level on a low-lying coast: land use planning for wetlands

USGS Publications Warehouse

Larsen, Curt; Clark, Inga; Guntenspergen, Glenn; Cahoon, Don; Caruso, Vincent; Hupp, Cliff; Yanosky, Tom

2004-01-01

The Blackwater National Wildlife Refuge (BNWR), on the Eastern Shore of Chesapeake Bay (figure 1), occupies an area less than 1 meter above sea level. The Refuge has been featured prominently in studies of the impact of sea level rise on coastal wetlands. Most notably, the refuge has been sited by the Intergovernmental Panel on Climate Change (IPCC) as a key example of 'wetland loss' attributable to rising sea level due to global temperature increase. Comparative studies of aerial photos taken since 1938 show an expanding area of open water in the central area of the refuge. The expanding area of open water can be shown to parallel the record of sea level rise over the past 60 years. The U.S. Fish and Wildlife Service (FWS) manages the refuge to support migratory waterfowl and to preserve endangered upland species. High marsh vegetation is critical to FWS waterfowl management strategies. A broad area once occupied by high marsh has decreased with rising sea level. The FWS needs a planning tool to help predict current and future areas of high marsh available for waterfowl. 'Wetland loss' is a relative term. It is dependant on the boundaries chosen for measurement. Wetland vegetation, zoned by elevation and salinity (figure 3), respond to rising sea level. Wetlands migrate inland and upslope and may vary in areas depending on the adjacent land slopes. Refuge managers need a geospatial tool that allows them to predict future areas that will be converted to high and intertidal marsh. Shifts in location and area of coverage must be anticipated. Viability of a current marsh area is also important. When will sea level rise make short-term management strategies to maintain an area impractical? The USGS has developed an inundation model for the BNWR centered on the refuge and surrounding areas. Such models are simple in concept, but they require a detailed topographic map upon which to superimpose future sea level positions. The new system of LIDAR mapping of land and shallow water surfaces has solved this problem. Our team has developed a detailed LIDAR map of the BNWR area at a 30 centimeter (ca. 1 ft) contour interval (figure 2). The new map allows us to identify the present marsh vegetation zones and to predict the location and area of future zones on a decade-by- decade basis over the next century at increments of sea level rise on the order of 3 cm/decade (ca. 1 inch). We have developed two scenarios for the model. The first is a steady-state model that uses the historic rate of sea level rise of 3.1 mm/yr to predict marsh areas. The second is a 'global warming' scenario utilizing a conservative IPCC model with an exponentially-increasing rate of sea level rise. Under either scenario, the BNWR is progressively inundated with an expanding core of open water. Although their positions change in the future, the areas of intertidal marsh as well as those of the critical high marsh remain fairly constant until the year 2050. Beyond that time, the low-lying land surface is overtopped by rising sea level and the area is dominated by open water. Our model suggests that wetland habitat in the Blackwater area might be maintained and sustained through a combination of public and private preservation efforts through easements in combination with judicious Federal land acquisition into the predicted areas of suitable marsh formation - but for only the next 50 years. Beyond that time much of this area will become open water.

Spatiotemporal Patterns of Evapotranspiration in Response to Multiple Environmental Factors Simulated by the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xiaoying; Mao, Jiafu; Thornton, P.

Spatiotemporal patterns of evapotranspiration (ET) over the period from 1982 to 2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates. We find that climate dominates the predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, and replaces climate to function as the dominant factor controlling ET changes over the North America, South America and Asia regions. Comparedmore » to the effect of climate and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. The aerosol deposition contribution is the third most important factor for trends of ET over Europe, while it has the smallest impact over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

Future probabilities of coastal floods in Finland

NASA Astrophysics Data System (ADS)

Pellikka, Havu; Leijala, Ulpu; Johansson, Milla M.; Leinonen, Katri; Kahma, Kimmo K.

2018-04-01

Coastal planning requires detailed knowledge of future flooding risks, and effective planning must consider both short-term sea level variations and the long-term trend. We calculate distributions that combine short- and long-term effects to provide estimates of flood probabilities in 2050 and 2100 on the Finnish coast in the Baltic Sea. Our distributions of short-term sea level variations are based on 46 years (1971-2016) of observations from the 13 Finnish tide gauges. The long-term scenarios of mean sea level combine postglacial land uplift, regionally adjusted scenarios of global sea level rise, and the effect of changes in the wind climate. The results predict that flooding risks will clearly increase by 2100 in the Gulf of Finland and the Bothnian Sea, while only a small increase or no change compared to present-day conditions is expected in the Bothnian Bay, where the land uplift is stronger.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Analysis of X-15 Landing Approach and Flare Characteristics Determined from the First 30 Flights

NASA Technical Reports Server (NTRS)

Matranga, Gene J.

1961-01-01

The approach and flare maneuvers for the first 30 flights of the X-15 airplane and the various control problems encountered are discussed. The results afford a relatively good cross section of landing conditions that might be experienced with future glide vehicles having low lift-drag ratios. Flight-derived drag data show that preflight predictions based on wind-tunnel tests were, in general, somewhat higher than the values measured in flight. Depending on configuration, the peak lift-drag ratios from flight varied from 3.5 to 4.5 as compared with a predicted range of from 3.0 to 4.2. By employing overhead, spiral-type patterns beginning at altitudes as high as 40,000 feet, the pilots were consistently able to touch down within about +/-1,000 feet of a designated point. A typical flare was initiated at a "comfortable" altitude of about 800 feet and an indicated airspeed of approximately 300 knots., which allowed a margin of excess speed. The flap and gear were extended when the flare was essentially completed, and an average touchdown was accomplished at a speed of about 185 knots indicated airspeed, an angle of attack of about 7 deg, and a rate of descent of about 4 feet per second. In general, the approach and landing characteristics were predicted with good accuracy in extensive preflight simulations. F-104 airplanes which simulated the X-15 landing characteristics were particularly valuable for pilot training.

Different fire-climate relationships on forested and non-forested landscapes in the Sierra Nevada ecoregion

USGS Publications Warehouse

Keeley, Jon E.; Syphard, Alexandra D.

2015-01-01

In the California Sierra Nevada region, increased fire activity over the last 50 years has only occurred in the higher-elevation forests on US Forest Service (USFS) lands, and is not characteristic of the lower-elevation grasslands, woodlands and shrublands on state responsibility lands (Cal Fire). Increased fire activity on USFS lands was correlated with warmer and drier springs. Although this is consistent with recent global warming, we found an equally strong relationship between fire activity and climate in the first half of the 20th century. At lower elevations, warmer and drier conditions were not strongly tied to fire activity over the last 90 years, although prior-year precipitation was significant. It is hypothesised that the fire–climate relationship in forests is determined by climatic effects on spring and summer fuel moisture, with hotter and drier springs leading to a longer fire season and more extensive burning. In contrast, future fire activity in the foothills may be more dependent on rainfall patterns and their effect on the herbaceous fuel load. We predict spring and summer warming will have a significant impact on future fire regimes, primarily in higher-elevation forests. Lower elevation ecosystems are likely to be affected as much by global changes that directly involve land-use patterns as by climate change.

Protecting Future Biodiversity via Re-allocation of Future Land-use Change Patterns

NASA Astrophysics Data System (ADS)

Chini, L. P.; Hurtt, G. C.; Jantz, S.; Brooks, T.; Leon, C.; Waldhoff, S.; Edmonds, J.

2013-12-01

Future scenarios, such as the Representative Concentration Pathways (RCPs), are typically designed to meet a radiative forcing target while also producing enough food and energy for a growing population. In the assessment process, impacts of these scenarios for other important variables such as biodiversity loss are considered 'downstream', after the future climate has been simulated within Earth System Models. However, the direct land-use impacts associated with future scenarios often have as much impact on these issues as the changing climate; in addition, many different patterns of land-use can result in the same radiative forcing target. In the case of biodiversity loss, one of the greatest contributors to species extinction is the loss of habitat such as primary forest, which is a direct result of land-use change decisions. By considering issues such as the preservation of future biodiversity 'up-front' in the scenario process, we can design a scenario that not only meets a radiative forcing target and feeds a growing planet, but also preserves as much habitat as possible through careful spatial allocation of future land-use change. Our Global Land-use Model (GLM) is used to provide 'harmonized' land-use data for the RCP process. GLM preserves as much information as possible from the Integrated Assessment Models (IAMs) while spatially allocating regional IAM land-use change data, ensuring a continuous transition from historical to future land-use states, and producing annual, gridded (0.5°×0.5°), fractional land-use states and all associated transitions. In this presentation we will present results from new GLM simulations in which land-use change decisions are constrained to meet the mutual goals of protecting important eco-regions (e.g. biodiversity hotspots) from future land-use change, providing enough food and fiber for a growing planet, and remaining consistent with the radiative forcing targets of the future scenarios. Trade-offs between agricultural demand and biodiversity protection were needed in some scenarios, but by constraining the land-use decisions to protect future biodiversity, an estimated 10-25% of species could be saved from loss between 2005 and 2100 (Jantz et al. 2013, in prep).

Potential future land use threats to California's protected areas

USGS Publications Warehouse

Wilson, Tamara Sue; Sleeter, Benjamin Michael; Davis, Adam Wilkinson

2015-01-01

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California’s protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California’s twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006–2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California’s Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices.

Projection of global terrestrial nitrous oxide emission using future scenarios of climate and land-use management

NASA Astrophysics Data System (ADS)

Inatomi, M. I.; Ito, A.

2016-12-01

Nitrous oxide (N2O), with a centennial mean residence time in the atmosphere, is one of the most remarkable greenhouse gases. Because natural and anthropogenic emissions make comparable contributions, we need to take account of different sources of N2O such as natural soils and fertilizer in croplands to predict the future emission change and to discuss its mitigation. In this study, we conduct a series of simulations of future change in nitrous oxide emission from terrestrial ecosystems using a process-based model, VISIT. We assume a couple of scenarios of future climate change, atmospheric nitrogen deposition, fertilizer input, and land-use change. In particular, we develop a new scenario of cropland fertilizer input on the basis of changes in crop productivity and fertilizer production cost. Expansion of biofuel crop production is considered but in a simplified manner (e.g., a specific fraction of pasture conversion to biofuel cultivation). Regional and temporal aspects of N2O emission are investigated and compared with previous studies. Finally, we make discussions, on the basis of simulated results, about the high-end of N2O emission, mitigation options, and impact of fertilizer input.

Future land use threats to range-restricted fish species in the United States

DOE PAGES

Januchowski-Hartley, Stephanie R.; Holtz, Lauren A.; Martinuzzi, Sebastian; ...

2016-03-04

Land use change is one major threat to freshwater biodiversity, and land use change scenarios can help to assess threats from future land use change, thereby guiding proactive conservation decisions. Furthermore, our goal was to identify which range-restricted freshwater fish species are most likely to be affected by land use change and to determine where threats to these species from future land use change in the conterminous United States are most pronounced.

Future land use threats to range-restricted fish species in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Januchowski-Hartley, Stephanie R.; Holtz, Lauren A.; Martinuzzi, Sebastian

Land use change is one major threat to freshwater biodiversity, and land use change scenarios can help to assess threats from future land use change, thereby guiding proactive conservation decisions. Furthermore, our goal was to identify which range-restricted freshwater fish species are most likely to be affected by land use change and to determine where threats to these species from future land use change in the conterminous United States are most pronounced.

Transient simulations of nitrogen load for a coastal aquifer and embayment, Cape Cod, MA

USGS Publications Warehouse

Colman, J.A.; Masterson, J.P.

2008-01-01

A time-varying, multispecies, modular, three-dimensional transport model (MT3DMS) was developed to simulate groundwater transport of nitrogen from increasing sources on land to the shore of Nauset Marsh, a coastal embayment of the Cape Cod National Seashore. Simulated time-dependent nitrogen loads at the coast can be used to correlate with current observed coastal eutrophic effects, to predict current and ultimate effects of development, and to predict loads resulting from source remediation. A time-varying nitrogen load, corrected for subsurface loss, was applied to the land subsurface in the transport model based on five land-use coverages documenting increasing development from 1951 to 1999. Simulated nitrogen loads to Nauset Marsh increased from 230 kg/yr before 1930 to 4390 kg/yr in 2001 to 7130 kg/yr in 2100, assuming future nitrogen sources constant at the 1999 land-use rate. The simulated nitrogen load per area of embayment was 5 times greater for Salt Pond, a eutrophic landward extension of Nauset Marsh, than for other Nauset Marsh areas. Sensitivity analysis indicated that load results were little affected by changes in vertical discretization and annual recharge but much affected by the nitrogen loss rate assumed for a kettle lake downgradient from a landfill.

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake sincemore » 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Association of outdoor recreation availability with physical activity and weight status in Minnesota youth.

PubMed

Wilhelm Stanis, Sonja A; Oftedal, Andrew; Schneider, Ingrid

2014-03-01

Examine macro-level associations of youth physical activity (PA) and weight status with availability of outdoor recreation resources (i.e., parkland, forestland, natural preserves, nonmotorized trails, and motorized trails) across counties in Minnesota. Hierarchical regression models examined if availability of recreation resources significantly improved prediction of PA and weight status of 9th and 12th grade boys and girls (2010) across Minnesota counties. The inclusion of county-level densities of recreational land variables did not produce a significant increase in R(2) for any of the models predicting 9th grade outcomes, yet county-level densities of recreational trails did significantly increase R(2) for both levels of PA and weight status. In contrast, the inclusion of recreational trails did not produce any significant increases in R(2) for 12th grade outcomes, although the inclusion of recreational land did significantly increase the R(2) for 12th grade girls achieving 30min of PA 5 or more days of the week. Findings indicate that various recreational land and trail types may have different impacts on and associations with PA and health outcomes. As such, it is important that future studies focus not only on parks, but also on other types of recreational lands and trails as well. Copyright © 2013 Elsevier Inc. All rights reserved.

Enhancing the Global Carbon Sink: A Key Mitigation Strategy

NASA Astrophysics Data System (ADS)

Torn, M. S.

2016-12-01

Earth's terrestrial ecosystems absorb about one-third of all anthropogenic CO2 emissions from the atmosphere each year, greatly reducing the climate forcing those emissions would otherwise cause. This puts the size of the terrestrial carbon sink on par with the most aggressive climate mitigation measures proposed. Moreover, the land sink has been keeping pace with rising emissions and has roughly doubled over the past 40 years. But there is a fundamental lack of understanding of why the sink has been increasing and what its future trajectory could be. In developing climate mitigation strategies, governments have a very limited scientific basis for projecting the contributions of their domestic sinks, and yet at least 117 of the 160 COP21 signatories stated they will use the land sink in their Nationally Defined Contribution (NDC). Given its potentially critical role in reducing net emissions and the importance of UNFCCC land sinks in future mitigation scenarios, a first-principles understanding of the dynamics of the land sink is needed. For expansion of the sink, new approaches and ecologically-sound technologies are needed. Carefully conceived terrestrial carbon sequestration could have multiple environmental benefits, but a massive expansion of land carbon sinks using conventional approaches could place excessive demands on the world's land, water, and fertilizer nutrients. Meanwhile, rapid climatic change threatens to undermine or reverse the sink in many ecosystems. We need approaches to protect the large sinks that are currently assumed useful for climate mitigation. Thus we highlight the need for a new research agenda aimed at predicting, protecting, and enhancing the global carbon sink. Key aspects of this agenda include building a predictive capability founded on observations, theory and models, and developing ecological approaches and technologies that are sustainable and scalable, and potentially provide co-benefits such as healthier soils, more resilient and productive ecosystems, and more carbon-neutral bioenergy. Better scientific understanding of the sink provides more options for policy design, enables mitigation strategies that capture co-benefits, and increases the chances that global mitigation commitments will be met.

The influence of current and future climate on the spatial distribution of coccidioidomycosis in the southwestern United States

NASA Astrophysics Data System (ADS)

Gorris, M. E.; Hoffman, F. M.; Zender, C. S.; Treseder, K. K.; Randerson, J. T.

2017-12-01

Coccidioidomycosis, otherwise known as valley fever, is an infectious fungal disease currently endemic to the southwestern U.S. The magnitude, spatial distribution, and seasonality of valley fever incidence is shaped by variations in regional climate. As such, climate change may cause new communities to become at risk for contracting this disease. Humans contract valley fever by inhaling fungal spores of the genus Coccidioides. Coccidioides grow in the soil as a mycelium, and when stressed, autolyze into spores 2-5 µm in length. Spores can become airborne from any natural or anthropogenic soil disturbance, which can be exacerbated by dry soil conditions. Understanding the relationship between climate and valley fever incidence is critical for future disease risk management. We explored several multivariate techniques to create a predictive model of county-level valley fever incidence throughout the southwestern U.S., including Arizona, California, New Mexico, Nevada, and Utah. We incorporated surface air temperature, precipitation, soil moisture, surface dust concentrations, leaf area index, and the amount of agricultural land, all of which influence valley fever incidence. A log-linear regression model that incorporated surface air temperature, soil moisture, surface dust concentration, and the amount of agricultural land explained 34% of the county-level variance in annual average valley fever incidence. We used this model to predict valley fever incidence for the Representative Concentration Pathway 8.5 using simulation output from the Community Earth System Model. In our analysis, we describe how regional hotspots of valley fever incidence may shift with sustained warming and drying in the southwestern U.S. Our predictive model of valley fever incidence may help mitigate future health impacts of valley fever by informing health officials and policy makers of the climate conditions suitable for disease outbreak.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

PubMed

Rosa, Isabel M D; Ahmed, Sadia E; Ewers, Robert M

2014-06-01

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline. © 2014 John Wiley & Sons Ltd.

Tree cover and aridity projections to 2060: a technical document supporting the Forest Service 2010 RPA assessment

Treesearch

Eric J. Greenfield; David J. Nowak

2013-01-01

Future projections of tree cover and climate change are useful to natural resource managers as they illustrate potential changes to our natural resources and the ecosystem services they provide. This report a) details three projections of tree cover change across the conterminous United States based on predicted land-use changes from 2000 to 2060; b) evaluates nine...

Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios

NASA Astrophysics Data System (ADS)

Wilson, T. S.; Sleeter, B. M.; Sherba, J.; Cameron, D.

2014-12-01

Human land use will increasingly contribute to habitat losses and water shortages in California, given future population projections and associated demand for agricultural land. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km2) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within the Mediterranean California ecoregion. Historical land use change estimates were derived from the Farmland Mapping and Monitoring Program (FMMP) dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources (CDWR). Six future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's (IPCC) Special Report on Emission Scenarios (SRES) A2 and B1 scenarios. Resulting spatial land-use scenario outputs were combined based on scenario agreement and a land conversion threat index developed to evaluate vulnerability of existing protected areas. Modeled scenario output of county-level agricultural water use data were also summarized, enabling examination of alternative water use futures. We present results of two separate applications of STSM of land-use change, demonstrating the utility of STSM in analyzing land-use related impacts on water resources as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, land-use change impacts will help to better inform resource management and mitigation strategies.

Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

NASA Astrophysics Data System (ADS)

Mei, Zhixiong; Wu, Hao; Li, Shiyun

2018-06-01

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the simulated change sizes and locations of each land-use type under different scenarios. The results not only demonstrate the validity of the improved model but also provide a valuable reference for relevant policy-makers.

Climate change adaptation via targeted ecosystem service provision: a sustainable land management strategy for the Segura catchment (SE Spain)

NASA Astrophysics Data System (ADS)

Zagaria, Cecilia; de Vente, Joris; Perez-Cutillas, Pedro

2014-05-01

Topical research investigating climate, land-use and management scenarios in the Segura catchment (SE Spain), depicts a landscape at high-risk of, quite literally, deserting agriculture. Land degradation in the semi-arid region of SE Spain is characterized by water shortage, high erosion rates and salinization, increasingly exacerbated by climatic changes, scarce vegetation cover and detrimental farming practices. Future climate scenarios predict increases in aridity, variability and intensity of rainfall events, leading to increasing pressure on scarce soil and water resources. This study conceptualized the impending crisis of agro-ecological systems of the Segura basin (18800 km2) as a crisis of ecosystem service deterioration. In light of existing land degradation drivers and future climate scenarios, the potential of Sustainable Land Management (SLM) strategies was evaluated to target three priority ecosystem services (water provision, sediment retention and carbon sequestration) as a means to achieve climate change adaptation and mitigation. A preceding thorough process of stakeholder engagement (as part of the EU funded DESIRE project) indicated five SLM technologies for potential implementation, all with a focus upon reducing soil erosion, increasing soil water holding capacity and soil organic matter content. These technologies have been tested for over four years in local experimental field plots, and have provided results on the local effects upon individual environmental parameters. Despite the growing emphasis witnessed in literature upon the context-specificity which characterizes adaptation solutions, the frequent analysis at the field scale is limited in both scope and utility. There is a need to investigate the effects of adaptive SLM solutions at wider, regional scales. Thus, this study modeled the cumulative effect of each of the five selected SLM technologies with InVEST, a spatial analyst tool designed for ecosystem service quantification and valuation. Scenario impacts upon the three prioritized ecosystem services were evaluated under present and expected future climate conditions (IPCC A1B scenario storyline for 2050) using ensemble regional climate model predictions. Results are given for both the entire Segura catchment as well as for delineated sub-catchments. This study's value lies in providing relevant stakeholders with quantitative information upon which SLM strategies result in greatest ecosystem service provision and tradeoffs, and thus greatest resilience to expected climate change impacts. Furthermore, this research hopes to contribute towards the mainstreaming of the ecosystem services concept in land management policy and research, and thus to familiarize relevant stakeholders with the concept, facilitating scaling-up processes by communicating the necessity and a means to successfully achieve climate adaptation.

43 CFR 3120.7 - Future interest.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Future interest. 3120.7 Section 3120.7 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT... interest. ...

Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods

USGS Publications Warehouse

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2014-02-13

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Evaluating Coastal Landscape Response to Sea-Level Rise in the Northeastern United States - Approach and Methods

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2015-01-01

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Land-use planning: One geologist's viewpoint

USGS Publications Warehouse

Zen, E.-A.

1983-01-01

Planning for the best use of land and its resources should take fully into consideration the long-term consequences of each type of use in order to stretch out most beneficially the well-being of society in the future, and to protect the integrity of the land and its biota. Three kinds of land-use can be distinguished for planning purposes. Reversible land-use leaves the land, after use, essentially as it was before; little or no man-induced modification remains. An example of reversible use in the United States is the designation of certain public lands as Wilderness. Terminal land-use commits the land to a chosen particular use, and any attempt at reversal requires either time-scales that are long compared with the expected lifespan of the social and political institution, or a commitment of resources that is too high for society to consider worth bearing. Examples of terminal land-use are location of metropolises and sites of toxic and/or radioactive waste disposals; by its nature the list grows monotonically. A current source of some social tension arises from the fact that Wilderness designation appears to assign a terminal-use status by legislative fiat, whereas in fact the land is being used reversibly. In between these two extremes of reversible and terminal land-use, the bulk of land-use is sequential, in which each use of land changes its potentials and configurations, and these changes are mainly irreversible. One goal of geologic input to land-use planning is to identify the various pathways along which a given land may be used, in order to extract the greatest benefit to society with the least harm to the land and its life. The proposed planning format consists of identification of (1) types of land, (2) types of use, (3) nature of consumption of resources when (2) acts upon (1), (4) identification of alternative pathways of land recovery to the original or some new state, and (5) due consideration of potentials for future use. Some consumptions are tangible; others, such as consumption of future options, are not. However, all must be considered in deciding how the land should be used, and both internal and environmental costs need to be included in the planning. Predictive methodology for land-use planning and for estimations of uncertainties must be developed to allow for the needs and consequences of both land-use and land recovery. Hardin (1968) spoke of the tragedy of the commons; White (1967) discussed the constraints of the western cultural heritage on our attitude towards our land and its resources. Land-use presents an archetype of the problem of the commons; only by community awareness of the dire consequences of the latent tragedy can effective societal action begin for the stewardship of the commons. Land-use decisions involve value judgement and are problems without technical solutions; but they require technical input, and earth scientists have a major role to play in both providing the input and in pointing out the implications of alternative decisions. ?? 1983.

Assessing development pressure in the Chesapeake Bay watershed: An evaluation of two land-use change models

USGS Publications Warehouse

Claggett, Peter; Jantz, Claire A.; Goetz, S.J.; Bisland, C.

2004-01-01

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations. ?? 2004 Kluwer Academic Publishers.

Assessing development pressure in the Chesapeake Bay watershed: an evaluation of two land-use change models.

PubMed

Claggett, Peter R; Jantz, Claire A; Goetz, Scott J; Bisland, Carin

2004-06-01

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations.

Arctic-COLORS (Coastal Land Ocean Interactions in the Arctic) - a NASA field campaign scoping study to examine land-ocean interactions in the Arctic

NASA Astrophysics Data System (ADS)

Hernes, P.; Tzortziou, M.; Salisbury, J.; Mannino, A.; Matrai, P.; Friedrichs, M. A.; Del Castillo, C. E.

2014-12-01

The Arctic region is warming faster than anywhere else on the planet, triggering rapid social and economic changes and impacting both terrestrial and marine ecosystems. Yet our understanding of critical processes and interactions along the Arctic land-ocean interface is limited. Arctic-COLORS is a Field Campaign Scoping Study funded by NASA's Ocean Biology and Biogeochemistry Program that aims to improve understanding and prediction of land-ocean interactions in a rapidly changing Arctic coastal zone, and assess vulnerability, response, feedbacks and resilience of coastal ecosystems, communities and natural resources to current and future pressures. Specific science objectives include: - Quantify lateral fluxes to the arctic inner shelf from (i) rivers and (ii) the outer shelf/basin that affect biology, biodiversity, biogeochemistry (i.e. organic matter, nutrients, suspended sediment), and the processing rates of these constituents in coastal waters. - Evaluate the impact of the thawing of Arctic permafrost within the river basins on coastal biology, biodiversity and biogeochemistry, including various rates of community production and the role these may play in the health of regional economies. - Assess the impact of changing Arctic landfast ice and coastal sea ice dynamics. - Establish a baseline for comparison to future change, and use state-of-the-art models to assess impacts of environmental change on coastal biology, biodiversity and biogeochemistry. A key component of Arctic-COLORS will be the integration of satellite and field observations with coupled physical-biogeochemical models for predicting impacts of future pressures on Arctic, coastal ocean, biological processes and biogeochemical cycles. Through interagency and international collaborations, and through the organization of dedicated workshops, town hall meetings and presentations at international conferences, the scoping study engages the broader scientific community and invites participation of experts from a wide range of disciplines, to refine our science objectives and outline detailed research strategies needed to attain these objectives. The deliverable will be a comprehensive report to NASA outlining the major scientific questions, and developing the initial study design and implementation concept.

Interfacing models of wildlife habitat and human development to predict the future distribution of puma habitat

USGS Publications Warehouse

Burdett, Christopher L.; Crooks, Kevin R.; Theobald, David M.; Wilson, Kenneth R.; Boydston, Erin E.; Lyren, Lisa A.; Fisher, Robert N.; Vickers, T. Winston; Morrison, Scott A.; Boyce, Walter M.

2010-01-01

The impact of human land uses on ecological systems typically differ relative to how extensively natural conditions are modified. Exurban development is intermediate-intensity residential development that often occurs in natural landscapes. Most species-habitat models do not evaluate the effects of such intermediate levels of human development and even fewer predict how future development patterns might affect the amount and configuration of habitat. We addressed these deficiencies by interfacing a habitat model with a spatially-explicit housing-density model to study the effect of human land uses on the habitat of pumas (Puma concolor) in southern California. We studied the response of pumas to natural and anthropogenic features within their home ranges and how mortality risk varied across a gradient of human development. We also used our housing-density model to estimate past and future housing densities and model the distribution of puma habitat in 1970, 2000, and 2030. The natural landscape for pumas in our study area consisted of riparian areas, oak woodlands, and open, conifer forests embedded in a chaparral matrix. Pumas rarely incorporated suburban or urban development into their home ranges, which is consistent with the hypothesis that the behavioral decisions of individuals can be collectively manifested as population-limiting factors at broader spatial scales. Pumas incorporated rural and exurban development into their home ranges, apparently perceiving these areas as modified, rather than non-habitat. Overall, pumas used exurban areas less than expected and showed a neutral response to rural areas. However, individual pumas that selected for or showed a neutral response to exurban areas had a higher risk of mortality than pumas that selected against exurban habitat. Exurban areas are likely hotspots for puma-human conflict in southern California. Approximately 10% of our study area will transform from exurban, rural, or undeveloped areas to suburban or urban by 2030, and 35% of suitable puma habitat on private land in 1970 will have been lost by 2030. These land-use changes will further isolate puma populations in southern California, but the ability to visualize these changes had provided a new tool for developing proactive conservation solutions.

Characterizing the relationship between Asian tiger mosquito abundance and habitat in urban New Jersey

NASA Astrophysics Data System (ADS)

Ferwerda, Carolin

2009-12-01

Since its introduction to North America in 1987, the Asian tiger mosquito (Aedes albopictus) has spread rapidly. Due to its unique ecology and preference for container breeding sites, Ae. albopictus commonly inhabits urban/suburban areas and is often in close contact with humans. An aggressive pest, this mosquito species is a vector of multiple arboviruses. In order for mosquito control efforts to remain effective, control of this important vector must be guided by spatially explicit habitat models that aid in predicting mosquito outbreaks. Using linear regression, I determined the relationship between adult Ae. albopictus abundance and climate, census, and land use factors in nine urban/suburban study sites in central New Jersey. Systematically collected adult counts (females and males) from July to October 2008, served as estimates of abundance. Fine-scale land use/land cover data were obtained from object-oriented classifications of 2007 CIR orthophotos in Definiens eCognition. Mosquito abundance data were tested for spatial autocorrelation via Moran's I, semivariograms, and hotspot analysis in order to reveal consistent patterns in abundance. Spatial pattern analysis produced little evidence of consistent spatial autocorrelation, though several sites exhibited recurring hotspots, especially in areas near residential housing and vegetation. Stepwise multiple regression was able to explain 20-25 percent of variation in Ae. albopictus abundance at the 'backyard' or cell level and 72-78 percent of variation in abundance at the 'neighborhood' or study site level. Meteorological variables (temperature on the trap date and precipitation), census variables (vacant housing units and population density), and more detailed land use/land cover classes (deciduous woody vegetation, rights-of-way and vacant lots) were frequently selected in all eight models, though many other independent variables were included in the individual models. The results of the spatial statistics suggest that clustering may occur at a broader extent, while the superior predictive ability of the site level models over the finer grain cell level models supports this conclusion. Future work should focus on validating these models with 2009 field data and testing whether finer grain weather and census data enhance the models' predictive ability. Given the major differences between individual county models, future studies should further explore variations in Ae. albopictus habitat preferences in different geographic locations.

All Recent Mars Landers Have Landed Downrange - Are Mars Atmosphere Models Mis-Predicting Density?

NASA Technical Reports Server (NTRS)

Desai, Prasun N.

2008-01-01

All recent Mars landers (Mars Pathfinder, the two Mars Exploration Rovers Spirit and Opportunity, and the Mars Phoenix Lander) have landed further downrange than their pre-entry predictions. Mars Pathfinder landed 27 km downrange of its prediction [1], Spirit and Opportunity landed 13.4 km and 14.9 km, respectively, downrange from their predictions [2], and Phoenix landed 21 km downrange from its prediction [3]. Reconstruction of their entries revealed a lower density profile than the best a priori atmospheric model predictions. Do these results suggest that there is a systemic issue in present Mars atmosphere models that predict a higher density than observed on landing day? Spirit Landing: The landing location for Spirit was 13.4 km downrange of the prediction as shown in Fig. 1. The navigation errors upon Mars arrival were very small [2]. As such, the entry interface conditions were not responsible for this downrange landing. Consequently, experiencing a lower density during the entry was the underlying cause. The reconstructed density profile that Spirit experienced is shown in Fig. 2, which is plotted as a fraction of the pre-entry baseline prediction that was used for all the entry, descent, and landing (EDL) design analyses. The reconstructed density is observed to be less dense throughout the descent reaching a maximum reduction of 15% at 21 km. This lower density corresponded to approximately a 1- low profile relative to the dispersions predicted. Nearly all the deceleration during the entry occurs within 10- 50 km. As such, prediction of density within this altitude band is most critical for entry flight dynamics analyses and design (e.g., aerodynamic and aerothermodynamic predictions, landing location, etc.).

A Parameterization for Land-Atmosphere-Cloud Exchange (PLACE): Documentation and Testing of a Detailed Process Model of the Partly Cloudy Boundary Layer over Heterogeneous Land.

NASA Astrophysics Data System (ADS)

Wetzel, Peter J.; Boone, Aaron

1995-07-01

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

The Impact of Land-Atmosphere Coupling on the 2017 Northern Great Plains Drought

NASA Astrophysics Data System (ADS)

Roundy, J. K.; Santanello, J. A., Jr.

2017-12-01

In a changing climate, the potential for increased frequency and duration of drought implies devastating impacts on many aspects of society. The negative impacts of drought can be reduced through informing sustainable water management made possible by real-time monitoring and prediction. The refinement of forecast models is best realized through large-scale observation based datasets, yet there are few of these datasets currently available. The Coupling Drought Index (CDI) is a metric based on the persistence of Land-Atmosphere (L-A) coupling into distinct regimes derived from observations of the land and atmospheric state. The coupling regime persistence has been shown to relate to drought intensification and recovery and is the basis for the Coupling Statistical Model (CSM), which uses a Markov Chain framework to make statistical predictions. The CDI and CSM have been used to understand the predictability of L-A interactions in NCEP's Climate Forecasts System version 2 (CFSv2) and indicated that the forecasts exhibit strong biases in the L-A coupling that produced biases in the precipitation and limited the predictability of drought. The CDI can also be derived exclusively from satellite data which provides an observational large-scale metric of L-A coupling and drought evolution. This provides a unique observational tool for understanding the persistence and intensification of drought through land-atmosphere interactions. During the Spring and Summer of 2017, a drought developed over the Norther great plains that caused substantial agricultural losses in parts of Montana and North and South Dakota. In this work, we use satellite derived CDI to explore the impact of Land-Atmosphere Interactions on the persistence and intensification of the 2017 Northern Great Plains drought. To do this we analyze and quantify the change in CDI at various spatial and temporal scales and correlate these changes with other drought indicators including the U.S. Drought Monitor (http://droughtmonitor.unl.edu). The 2017 Northern Great Plains drought is compared to previous droughts in the region and the predictability of 2017 drought from the CSM as well as future droughts for the area is assessed.

Future habitat loss and extinctions driven by land-use change in biodiversity hotspots under four scenarios of climate-change mitigation.

PubMed

Jantz, Samuel M; Barker, Brian; Brooks, Thomas M; Chini, Louise P; Huang, Qiongyu; Moore, Rachel M; Noel, Jacob; Hurtt, George C

2015-08-01

Numerous species have been pushed into extinction as an increasing portion of Earth's land surface has been appropriated for human enterprise. In the future, global biodiversity will be affected by both climate change and land-use change, the latter of which is currently the primary driver of species extinctions. How societies address climate change will critically affect biodiversity because climate-change mitigation policies will reduce direct climate-change impacts; however, these policies will influence land-use decisions, which could have negative impacts on habitat for a substantial number of species. We assessed the potential impact future climate policy could have on the loss of habitable area in biodiversity hotspots due to associated land-use changes. We estimated past extinctions from historical land-use changes (1500-2005) based on the global gridded land-use data used for the Intergovernmental Panel on Climate Change Fifth Assessment Report and habitat extent and species data for each hotspot. We then estimated potential extinctions due to future land-use changes under alternative climate-change scenarios (2005-2100). Future land-use changes are projected to reduce natural vegetative cover by 26-58% in the hotspots. As a consequence, the number of additional species extinctions, relative to those already incurred between 1500 and 2005, due to land-use change by 2100 across all hotspots ranged from about 220 to 21000 (0.2% to 16%), depending on the climate-change mitigation scenario and biological factors such as the slope of the species-area relationship and the contribution of wood harvest to extinctions. These estimates of potential future extinctions were driven by land-use change only and likely would have been higher if the direct effects of climate change had been considered. Future extinctions could potentially be reduced by incorporating habitat preservation into scenario development to reduce projected future land-use changes in hotspots or by lessening the impact of future land-use activities on biodiversity within hotspots. © 2015 Society for Conservation Biology.

Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

NASA Astrophysics Data System (ADS)

Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.

2007-12-01

Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land use change disrupts the hydrological cycle through increasing the water yield at some places leading to floods while diminishing, or even eliminating the low flow at other places.

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

Meta-Analysis of Land Use / Land Cover Change Factors in the Conterminous US and Prediction of Potential Working Timberlands in the US South from FIA Inventory Plots and NLCD Cover Maps

NASA Astrophysics Data System (ADS)

Jeuck, James A.

This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products provide practical analytical tools for those interested in studying the area and distribution of PWT in the US South.

[Response of water yield function of ecosystem to land use change in Nansi Lake Basin based on CLUE-S model and InVEST model .

PubMed

Guo, Hong Wei; Sun, Xiao Yin; Lian, Li Shu; Zhang, Da Zhi; Xu, Yan

2016-09-01

Land use change has an important role in hydrological processes and utilization of water resources, and is the main driving force of water yield function of ecosystem. This paper analyzed the change of land use from 1990 to 2013 in Nansi Lake Basin, Shandong Province. The future land use in 2030 was also predicted and simulated by CLUE-S model. Based on land use scenarios, we analyzed the influence of land use change on ecosystem function of water yield in nearly 25 years through InVEST water yield model and spatial mapping. The results showed that the area of construction land increased by 3.5% in 2013 because of burgeoning urbanization process, but farmland area decreased by 2.4% which was conversed to construction land mostly. The simulated result of InVEST model suggested that water yield level of whole basin decreased firstly and increased subsequently during last 25 years and peaked at 232.1 mm in 2013. The construction land area would increase by 6.7% in 2030 based on the land use scenarios of fast urbanization, which would lead to a remarkable growth for water yield and risk of flowing flooding. However, the water yield level of whole basin would decrease by 1.2 % in 2013 if 300 meter-wide forest buffer strips around Nansi Lake were built up.

How Cities Make Their Own Weather

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in d e near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. We will also present results from experiments using a regional atmospheric-land surface modeling system. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

Impact of Land Use Management and Soil Properties on Denitrifier Communities of Namibian Savannas.

PubMed

Braker, Gesche; Matthies, Diethart; Hannig, Michael; Brandt, Franziska Barbara; Brenzinger, Kristof; Gröngröft, Alexander

2015-11-01

We studied potential denitrification activity and the underlying denitrifier communities in soils from a semiarid savanna ecosystem of the Kavango region in NE Namibia to help in predicting future changes in N(2)O emissions due to continuing changes of land use in this region. Soil type and land use (pristine, fallow, and cultivated soils) influenced physicochemical characteristics of the soils that are relevant to denitrification activity and N(2)O fluxes from soils and affected potential denitrification activity. Potential denitrification activity was assessed by using the denitrifier enzyme activity (DEA) assay as a proxy for denitrification activity in the soil. Soil type and land use influenced C and N contents of the soils. Pristine soils that had never been cultivated had a particularly high C content. Cultivation reduced soil C content and the abundance of denitrifiers and changed the composition of the denitrifier communities. DEA was strongly and positively correlated with soil C content and was higher in pristine than in fallow or recently cultivated soils. Soil type and the composition of both the nirK- and nirS-type denitrifier communities also influenced DEA. In contrast, other soil characteristics like N content, C:N ratio, and pH did not predict DEA. These findings suggest that due to greater availability of soil organic matter, and hence a more effective N cycling, the natural semiarid grasslands emit more N(2)O than managed lands in Namibia.

A multiyear study of soil moisture patterns across agricultural and forested landscapes

NASA Astrophysics Data System (ADS)

Georgakakos, C. B.; Hofmeister, K.; O'Connor, C.; Buchanan, B.; Walter, T.

2017-12-01

This work compares varying spatial and temporal soil moisture patterns in wet and dry years between forested and agricultural landscapes. This data set spans 6 years (2012-2017) of snow-free soil moisture measurements across multiple watersheds and land covers in New York State's Finger Lakes region. Due to the relatively long sampling period, we have captured fluctuations in soil moisture dynamics across wetter, dryer, and average precipitation years. We can therefore analyze response of land cover types to precipitation under varying climatic and hydrologic conditions. Across the study period, mean soil moisture in forest soils was significantly drier than in agricultural soils, and exhibited a smaller range of moisture conditions. In the drought year of 2016, soil moisture at all sites was significantly drier compared to the other years. When comparing the effects of land cover and year on soil moisture, we found that land cover had a more significant influence. Understanding the difference in landscape soil moisture dynamics between forested and agricultural land will help predict watershed responses to changing precipitation patterns in the future.

Cratering Soil by Impinging Jets of Gas, with Application to Landing Rockets on Planetary Surfaces

NASA Technical Reports Server (NTRS)

Metzger, Philip T.; Vu, B. T.; Taylor, D. E.; Kromann, M. J.; Fuchs, M.; Yutko, B.; Dokos, A.; Immer, Christopher D.; Lane, J. E.; Dunkel, Michael B.;

Multi-decadal trends in global terrestrial evapotranspiration and its components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yongqiang; Peña-Arancibia, Jorge L.; McVicar, Tim R.

In this study, evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (E t), direct evaporation from the soil (E s) and vaporization of intercepted rainfall from vegetationmore » (E i). During this period, ET over land has increased significantly (p < 0.01), caused by increases in E t and E i, which are partially counteracted by E s decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in E t over land is about twofold of the decrease in E s. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.« less

Multi-decadal trends in global terrestrial evapotranspiration and its components

DOE PAGES

Zhang, Yongqiang; Peña-Arancibia, Jorge L.; McVicar, Tim R.; ...

2016-01-11

In this study, evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (E t), direct evaporation from the soil (E s) and vaporization of intercepted rainfall from vegetationmore » (E i). During this period, ET over land has increased significantly (p < 0.01), caused by increases in E t and E i, which are partially counteracted by E s decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in E t over land is about twofold of the decrease in E s. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle.« less

Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Santos, Pablo; Medlin, Jeffrey M.; Jedlovec, Gary J.

2009-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF simulations over the Mobile, AL and Miami, FL NWS county warning areas. Future efforts may involve examining the impacts of assimilating remotely-sensed soil moisture data, and/or introducing weekly greenness vegetation fraction composites (as opposed to monthly climatologies) into ol'fline NASA LIS runs. Based on positive impacts, the offline LIS runs could be transitioned into an operational mode, providing land surface initialization data to NWS forecast offices in real time.

An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

NASA Astrophysics Data System (ADS)

Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

2014-05-01

Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are currently in development: (i) the socio-economic agent-based model SWISSland; (ii) a land management downscaling approach that provides crop rotation, fertilisers and pesticides application rates for each land management unit, and (iii) the agro-ecosystem model EPIC, which is currently being calibrated with long-term soil measurements and agricultural management data provided by the Swiss Soil Monitoring Network. Moreover, the IMF will make use of land cover information derived from remote sensing to continuously update predictions. The IMF will be tested on two case study regions to develop indicators of sustainable soil management that can be implemented into Swiss policies.

Historical and projected coastal Louisiana land changes: 1978-2050

USGS Publications Warehouse

Barras, John; Beville, Shelly; Britsch, Del; Hartley, Stephen; Hawes, Suzanne; Johnston, James; Kemp, Paul; Kinler, Quin; Martucci, Antonio; Porthouse, Jon; Reed, Denise; Roy, Kevin; Sapkota, Sijan; Suhayda, Joseph

2003-01-01

An important component of the Louisiana Coastal Area (LCA) Comprehensive Coastwide Ecosystem Restoration Study is the projection of a “future condition” for the Louisiana coast if no further restoration measures were adopted. Such a projection gives an idea of what the future might hold without implementation of the LCA plan and provides a reference against which various ecosystem restoration proposals can be assessed as part of the planning process. One of the most fundamental measures of ecosystem degradation in coastal Louisiana has been the conversion of land (mostly emergent vegetated habitat) to open water. Thus, the projection of the future condition of the ecosystem must be based upon the determination of future patterns of land and water. To conduct these projections, a multidisciplinary LCA Land Change Study Group was formed that included individuals from agencies and academia with expertise in remote sensing, geographic information systems (GIS), ecosystem processes, and coastal land loss. Methods were based upon those used in prior studies for Coast 2050 (Louisiana Coastal Wetlands Conservation and Restoration Task Force [LCWCRTF] and the Wetlands Conservation and Restoration Authority 1998, 1999) and modified as described here to incorporate an improved understanding of coastal land loss and land gain processes with more advanced technical capabilities. The basic approach is to use historical data to assess recent trends in land loss and land gain and to project those changes into the future, taking into account spatial variations in the patterns and rates of land loss and land gain. This approach is accomplished by developing a base map, assessing and delineating areas of similar land change (polygons), and projecting changes into the future. This report describes the methodology and compares the current land change projection to previous projections.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Regional Climate Change Impact on Agricultural Land Use in West Africa

NASA Astrophysics Data System (ADS)

Ahmed, K. F.; Wang, G.; You, L.

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes in land use pattern are robust.

Selecting reasonable future land use scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allred, W.E.; Smith, R.W.

1995-12-31

This paper examines a process to help select the most reasonable future land use scenarios for hazardous waste and/or low-level radioactive waste disposal sites. The process involves evaluating future land use scenarios by applying selected criteria currently used by commercial mortgage companies to determine the feasibility of obtaining a loan for purchasing such land. The basis for the process is that only land use activities for which a loan can be obtained will be considered. To examine the process, a low-level radioactive waste site, the Radioactive Waste Management Complex at the Idaho National Engineering Laboratory, is used as an example.more » The authors suggest that the process is a very precise, comprehensive, and systematic (common sense) approach for determining reasonable future use of land. Implementing such a process will help enhance the planning, decisionmaking, safe management, and cleanup of present and future disposal facilities.« less

Modeling the Effects of Climate Change on Whitebark Pine Along the Pacific Crest Trail

NASA Astrophysics Data System (ADS)

Anderson, R. S.; Nguyen, A.; Gill, N.; Kannan, S.; Patadia, N.; Meyer, M.; Schmidt, C.

2012-12-01

The Pacific Crest Trail (PCT), one of eight National Scenic Trails, stretches 2,650 miles from Mexico to the Canadian border. At high elevations along this trail, within Inyo and Sierra National Forests, populations of whitebark pine (Pinus albicaulis) have been diminishing due to infestation of the mountain pine beetle (Dendroctonus ponderosae) and are threatened due to a changing climate. Understanding the current and future condition of whitebark pine is a primary goal of forest managers due to its high ecological and economic importance, and it is currently a candidate for protection under the Endangered Species Act (ESA). Using satellite imagery, we analyzed the rate and spatial extent of whitebark pine tree mortality from 1984 to 2011 using the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) program. Climate data, soil properties, and biological features of the whitebark pine were incorporated in the Physiological Principles to Predict Growth (3-PG) model to predict future rates of growth and assess its applicability in modeling natural whitebark pine processes. Finally, the Random Forest algorithm was used with topographic data alongside recent and future climate data from the IPCC A2 and B1 climate scenarios for the years 2030, 2060, and 2090 to model the future distribution of whitebark pine. LandTrendr results indicate beetle related mortality covering 14,940 km2 of forest, 2,880 km2 of which are within whitebark pine forest. By 2090, our results show that under the A2 climate scenario, whitebark pine suitable habitat may be reduced by as much as 99.97% by the year 2090 within our study area. Under the B1 climate scenario, which has decreased CO2 emissions, 13.54% more habitat would be preserved in 2090.

Long-term simulations of dissolved oxygen concentrations in Lake Trout lakes

NASA Astrophysics Data System (ADS)

Jabbari, A.; Boegman, L.; MacKay, M.; Hadley, K.; Paterson, A.; Jeziorski, A.; Nelligan, C.; Smol, J. P.

2016-02-01

Lake Trout are a rare and valuable natural resource that are threatened by multiple environmental stressors. With the added threat of climate warming, there is growing concern among resource managers that increased thermal stratification will reduce the habitat quality of deep-water Lake Trout lakes through enhanced oxygen depletion. To address this issue, a three-part study is underway, which aims to: analyze sediment cores to understand the past, develop empirical formulae to model the present and apply computational models to forecast the future. This presentation reports on the computational modeling efforts. To this end, a simple dissolved oxygen sub-model has been embedded in the one-dimensional bulk mixed-layer thermodynamic Canadian Small Lake Model (CSLM). This model is currently being incorporated into the Canadian Land Surface Scheme (CLASS), the primary land surface component of Environment Canada's global and regional climate modelling systems. The oxygen model was calibrated and validated by hind-casting temperature and dissolved oxygen profiles from two Lake Trout lakes on the Canadian Shield. These data sets include 5 years of high-frequency (10 s to 10 min) data from Eagle Lake and 30 years of bi-weekly data from Harp Lake. Initial results show temperature and dissolved oxygen was predicted with root mean square error <1.5 °C and <3 mgL-1, respectively. Ongoing work is validating the model, over climate-change relevant timescales, against dissolved oxygen reconstructions from the sediment cores and predicting future deep-water temperature and dissolved oxygen concentrations in Canadian Lake Trout lakes under future climate change scenarios. This model will provide a useful tool for managers to ensure sustainable fishery resources for future generations.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Understanding the Role of Biology in the Global Environment: NASA'S Mission to Planet Earth

NASA Technical Reports Server (NTRS)

Townsend, William F.

1996-01-01

NASA has long used the unique perspective of space as a means of expanding our understanding of how the Earth's environment functions. In particular, the linkages between land, air, water, and life-the elements of the Earth system-are a focus for NASA's Mission to Planet Earth. This approach, called Earth system science, blends together fields like meteorology, biology, oceanography, and atmospheric science. Mission to Planet Earth uses observations from satellites, aircraft, balloons, and ground researchers as the basis for analysis of the elements of the Earth system, the interactions between those elements, and possible changes over the coming years and decades. This information is helping scientists improve our understanding of how natural processes affect us and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, an enhanced ability to predict how the climate will change in the future. NASA has designed Mission to Planet Earth to focus on five primary themes: Land Cover and Land Use Change; Seasonal to Interannual Climate Prediction; Natural Hazards; Long-Term Climate Variability; and Atmosphere Ozone.

43 CFR 3509.10 - What are future interest leases?

Code of Federal Regulations, 2012 CFR

2012-10-01

... Section 3509.10 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LEASING OF SOLID MINERALS OTHER THAN COAL... that will revert to the Federal Government at some future date. Future interest leases allow the...

43 CFR 3509.10 - What are future interest leases?

Code of Federal Regulations, 2011 CFR

2011-10-01

... Section 3509.10 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LEASING OF SOLID MINERALS OTHER THAN COAL... that will revert to the Federal Government at some future date. Future interest leases allow the...

Decision analysis and risk models for land development affecting infrastructure systems.

PubMed

Thekdi, Shital A; Lambert, James H

2012-07-01

Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

Increasing efficiency of CO2 uptake by combined land-ocean sink

NASA Astrophysics Data System (ADS)

van Marle, M.; van Wees, D.; Houghton, R. A.; Nassikas, A.; van der Werf, G.

2017-12-01

Carbon-climate feedbacks are one of the key uncertainties in predicting future climate change. Such a feedback could originate from carbon sinks losing their efficiency, for example due to saturation of the CO2 fertilization effect or ocean warming. An indirect approach to estimate how the combined land and ocean sink responds to climate change and growing fossil fuel emissions is based on assessing the trends in the airborne fraction of CO2 emissions from fossil fuel and land use change. One key limitation with this approach has been the large uncertainty in quantifying land use change emissions. We have re-assessed those emissions in a more data-driven approach by combining estimates coming from a bookkeeping model with visibility-based land use change emissions available for the Arc of Deforestation and Equatorial Asia, two key regions with large land use change emissions. The advantage of the visibility-based dataset is that the emissions are observation-based and this dataset provides more detailed information about interannual variability than previous estimates. Based on our estimates we provide evidence that land use and land cover change emissions have increased more rapidly than previously thought, implying that the airborne fraction has decreased since the start of CO2 measurements in 1959. This finding is surprising because it means that the combined land and ocean sink has become more efficient while the opposite is expected.

The importance of considering shifts in seasonal changes in discharges when predicting future phosphorus loads in streams

USGS Publications Warehouse

LaBeau, Meredith B.; Mayer, Alex S.; Griffis, Veronica; Watkins, David Jr.; Robertson, Dale M.; Gyawali, Rabi

2015-01-01

In this work, we hypothesize that phosphorus (P) concentrations in streams vary seasonally and with streamflow and that it is important to incorporate this variation when predicting changes in P loading associated with climate change. Our study area includes 14 watersheds with a range of land uses throughout the U.S. Great Lakes Basin. We develop annual seasonal load-discharge regression models for each watershed and apply these models with simulated discharges generated for future climate scenarios to simulate future P loading patterns for two periods: 2046–2065 and 2081–2100. We utilize output from the Coupled Model Intercomparison Project phase 3 downscaled climate change projections that are input into the Large Basin Runoff Model to generate future discharge scenarios, which are in turn used as inputs to the seasonal P load regression models. In almost all cases, the seasonal load-discharge models match observed loads better than the annual models. Results using the seasonal models show that the concurrence of nonlinearity in the load-discharge model and changes in high discharges in the spring months leads to the most significant changes in P loading for selected tributaries under future climate projections. These results emphasize the importance of using seasonal models to understand the effects of future climate change on nutrient loads.

A Scenario Based Assessment of Future Groundwater Resources in the Phoenix Active Management Area

NASA Astrophysics Data System (ADS)

Escobar, V. M.; Lant, T. W.

2007-12-01

The availability of future water supplies in central Arizona depends on the interaction of multiple physical and human systems: climate, hydrology, water and land-use policy, urbanization, and regulation. The problem in assessing future water supplies requires untangling these drivers and recasting the issue in a way that acknowledges the inherent uncertainties in climate and population growth predictions while offering meaningful metrics for outcomes under alternative scenarios. Further, the drivers, policy options, and outcomes are spatially heterogeneous - surface water supplies, new urban developments and changes in land-use will not be shared uniformly across the region. Consequently, different geographic regions of the Phoenix metropolitan area will be more vulnerable to shortages in water availability, and these potential vulnerabilities will be more or less severe depending on which factors cause the shortage. The results of this research will make several contributions to existing literature and research products for groundwater conservation and future urban planning. It will provide location specific metrics of water vulnerability and offer a novel approach to groundwater analysis; it will demonstrate the XLRM framework with an application to central Arizona Water resources. Lastly, it will add to the WaterSim climate model by spatializing the groundwater component for the Phoenix Active Management Area.

Assessing Hydrologic Impacts of Future Land Cover Change Scenarios in the San Pedro River (U.S./Mexico)

EPA Science Inventory

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed to characterize hydrologic impacts from future urban growth throug...

Assessing Hydrologic Impacts of Future Land Cover Change Scenarios in the South Platte River Basin (CO, WY, & NE)

EPA Science Inventory

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed to characterize hydrologic impacts from future urban growth throug...

Implication of Agricultural Land Use Change on Regional Climate Projection

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.

Soil erosion and associated organic carbon transfer along the southern Amazon land use frontier - status quo and future scenarios

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Herrmann, Anne-Kathrin; Herrmann, Marie-Kristin; Amorim, Ricardo S. S.; Schmidt, Jürgen

2016-04-01

The Southern Amazon deforestation arc is one of the world's most dynamically changing landscapes mainly caused by global demands on animal products. Already more than 50 % of the savanna vegetation in Mato Grosso is converted to agricultural land. Following the BR-163 highway to the north deforestation is continuing, where former tropical rainforest is converted to pastures. Consequences are expected to be negative and highly relevant concerning soil functions. Soil losses and related carbon transfer by water erosion are likely to occur on a larger scale. Within the Carbiocial project, the impact of land use changes on soil loss was measured by applying artificial rainfall simulations. Experimental results were used to parameterize the physical based EROSION 3D simulation model in two meso-scale watersheds. The impact of future land use and climate scenarios on soil erosion and particle bound organic carbon transfer were simulated in addition to present day effects. Our results allow different predictions: Land use changes from natural vegetation to pasture lead to increased surface runoffs and soil losses. Due to the predominant no-tillage management, croplands do not reveal a similar behaviour; runoff and sediment yields are close to the initial level. Particle bound organic carbon losses are negligible compared to the removal of biomass during deforestation. Compared to the land use change effect more significant differences appear concerning the predominant soil types of the study region. Deterioration of soil functions are less pronounced for Ferralsols with a stable microstructure than for Acrisols. Additionally, our data suggest, that the main soil losses are related to the narrow time windows of land use conversion. Consequently, intensifying production on existing agricultural land rather than creating new production area (deforestation) might be the most practical way of preserving soils of the Southern Amazon.

A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Ning; Yearsley, John; Baptiste, Marisa

While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution.more » DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and climate change together are predicted to significantly increase annual mean streamflow (up to 55%), water temperature (up to 1.9 ºC), TSS load (up to 182%), and TP load (up to 74%).« less

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in Mancha Oriental (Spain)

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Peña-Haro, S.; Garcia-Prats, A.; Mocholi-Almudever, A. F.; Henriquez-Dole, L.; Macian-Sorribes, H.; Lopez-Nicolas, A.

2014-09-01

Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation, as various and complex interactions in the hydrological cycle take part. Land-use and land-cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands (global change). Changes in future climate and land uses will alter the hydrologic cycles and subsequently impact the quantity and quality of regional water systems. Predicting the behavior of recharge and discharge conditions under future climatic and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system in Spain, in the last decades the transformation from dry to irrigated lands has led to a significant drop of the groundwater table in one of the largest groundwater bodies in Spain, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Streamflow depletion is compromising the related ecosystems and the supply to the downstream demands, provoking a complex management issue. The intense use of fertilizer in agriculture is also leading to locally high groundwater nitrate concentrations. Understanding the spatial and temporal distribution of water availability and water quality is essential for a proper management of the system. In this paper we analyze the potential impact of climate and land use change in the system by using an integrated modelling framework consisting of the sequentially coupling of a watershed agriculturally-based hydrological model (SWAT) with the ground-water model MODFLOW and mass-transport model MT3D. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing ET and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3D inputs for assessing the fate and transport of nitrate leached from the topsoil. Results on river discharge, crop yields, groundwater levels and groundwater nitrate concentrations obtained from simulation fit well to the observed values. Three climate change scenarios have been considered, corresponding to 3 different GCMs for emission scenario A1B, covering the control period, and short, medium and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends by remote sensing images and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections have been used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. The results show the sensitivity of groundwater quantity and quality (nitrate pollution) to climate and land use changes, and the need to implement adaptation measures in order to prevent further groundwater level declines and increasing nitrate concentrations. The sequential modelling chain has been proved to be a valuable assessment and management tool for supporting the development of sustainable management strategies.

A historical land use data set for the Holocene; HYDE 3.2

NASA Astrophysics Data System (ADS)

Klein Goldewijk, Kees

2016-04-01

Land use plays an important role in the climate system (Feddema et al., 2005). Many ecosystem processes are directly or indirectly climate driven, and together with human driven land use changes, they determine how the land surface will evolve through time. To assess the effects of land cover changes on the climate system, models are required which are capable of simulating interactions between the involved components of the Earth system (land, atmosphere, ocean, and carbon cycle). Since driving forces for global environmental change differ among regions, a geographically (spatially) explicit modeling approach is called for, so that it can be incorporated in global and regional (climate and/or biophysical) change models in order to enhance our understanding of the underlying processes and thus improving future projections. Integrated records of the co-evolving human-environment system over millennia are needed to provide a basis for a deeper understanding of the present and for forecasting the future. This requires the major task of assembling and integrating regional and global historical, archaeological, and paleo-environmental records. Humans cannot predict the future. But, if we can adequately understand the past, we can use that understanding to influence our decisions and to create a better, more sustainable and desirable future. Some researchers suggest that mankind has shifted from living in the Holocene (~emergence of agriculture) into the Anthropocene (~humans capable of changing the Earth' atmosphere) since the start of the Industrial Revolution. But in the light of the sheer size and magnitude of some historical land use changes (e.g. collapse of the Roman Empire in the 4th century, the depopulation of Europe due to the Black Plague in the 14th century and the aftermath of the colonization of the Americas in the 16th century), some believe that this point might have occurred earlier in time (Ruddiman, 2003; Kaplan et al., 2010). Many uncertainties still remain today and gaps in our knowledge of the Antiquity and its aftermath can only be improved by interdisciplinary research, of which some examples will be given. Here I will present the latest update (v 3.2) of the History Database of the Global Environment (HYDE) (Klein Goldewijk et al., 2011) with new quantitative estimates of the underlying demographic and agricultural developments for the Holocene. References Feddema, J.J., Oleson, K.W., Bonan, G.B., Mearns, L.O., Buja, L.E., Meehl, G.A. & Washington, W.M. (2005) Atmospheric science: The importance of land-cover change in simulating future climates. Science, 310, 1674-1678. Kaplan, J.O., Krumhardt, K.M., Ellis, E.C., Ruddiman, W.F., Lemmen, C. & Klein Goldewijk, K. (2010) Holocene carbon emissions as a result of anthropogenic land cover change. The Holocene, 20, doi:10.1177/0959683610386983 Klein Goldewijk, K., Beusen, A., van Drecht, G. & de Vos, M. (2011) The HYDE 3.1 spatially explicit database of human induced land use change over the past 12,000 years. Global Ecology and Biogeography, 20, 73-86. Ruddiman, W.F. (2003) The anthropogenic greenhouse era began thousands of years ago. Climatic Change, 61, 261-293.

Conflation and aggregation of spatial data improve predictive models for species with limited habitats: a case of the threatened yellow-billed cuckoo in Arizona, USA

USGS Publications Warehouse

Villarreal, Miguel L.; van Riper, Charles; Petrakis, Roy E.

2013-01-01

Riparian vegetation provides important wildlife habitat in the Southwestern United States, but limited distributions and spatial complexity often leads to inaccurate representation in maps used to guide conservation. We test the use of data conflation and aggregation on multiple vegetation/land-cover maps to improve the accuracy of habitat models for the threatened western yellow-billed cuckoo (Coccyzus americanus occidentalis). We used species observations (n = 479) from a state-wide survey to develop habitat models from 1) three vegetation/land-cover maps produced at different geographic scales ranging from state to national, and 2) new aggregate maps defined by the spatial agreement of cover types, which were defined as high (agreement = all data sets), moderate (agreement ≥ 2), and low (no agreement required). Model accuracies, predicted habitat locations, and total area of predicted habitat varied considerably, illustrating the effects of input data quality on habitat predictions and resulting potential impacts on conservation planning. Habitat models based on aggregated and conflated data were more accurate and had higher model sensitivity than original vegetation/land-cover, but this accuracy came at the cost of reduced geographic extent of predicted habitat. Using the highest performing models, we assessed cuckoo habitat preference and distribution in Arizona and found that major watersheds containing high-probably habitat are fragmented by a wide swath of low-probability habitat. Focus on riparian restoration in these areas could provide more breeding habitat for the threatened cuckoo, offset potential future habitat losses in adjacent watershed, and increase regional connectivity for other threatened vertebrates that also use riparian corridors.

Predicted net efflux of radiocarbon from the ocean and increase in atmospheric radiocarbon content

NASA Astrophysics Data System (ADS)

Caldeira, Ken; Rau, Greg H.; Duffy, Philip B.

Prior to changes introduced by man, production of radiocarbon (14C) in the stratosphere nearly balanced the flux of 14C from the atmosphere to the ocean and land biosphere, which in turn nearly balanced radioactive decay in these 14C reservoirs. This balance has been altered by land-use changes, fossil-fuel burning, and atmospheric nuclear detonations. Here, we use a model of the global carbon cycle to quantify these radiocarbon fluxes and make predictions about their magnitude in the future. Atmospheric nuclear detonations increased atmospheric 14C content by about 80% by the mid-1960's. Since that time, the 14C content of the atmosphere has been diminishing as this bomb radiocarbon has been entering the oceans and terrestrial biosphere. However, we predict that atmospheric 14C content will reach a minimum and start to increase within the next few years if fossil-fuel burning continues according to a “business-as-usual” scenario, even though fossil fuels are devoid of 14C. This will happen because fossil-fuel carbon diminishes the net flux of 14C from the atmosphere to the oceans and land biosphere, forcing 14C to accumulate in the atmosphere. Furthermore, the net flux of both bomb and natural 14C into the ocean are predicted to continue to slow and then, in the middle of the next century, to reverse, so that there will be a net flux of 14C from the ocean to the atmosphere. The predicted reversal of net 14C fluxes into the ocean is a further example of human impacts on the global carbon cycle.

A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios.

PubMed

Chen, Min; Melaas, Eli K; Gray, Josh M; Friedl, Mark A; Richardson, Andrew D

2016-11-01

A spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf-out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km 2 ), we found that the revised model substantially outperformed the standard CLM seasonal-deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long-term trends (1950-2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf-out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf-out in colder regions, but later leaf-out in warmer regions, and no trend globally. The earlier spring leaf-out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr -1 ) and evapotranspiration (up to 24 mm yr -1 ) when results were integrated across the study region. These results suggest that the standard seasonal-deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land-atmosphere interactions and feedbacks may result. © 2016 John Wiley & Sons Ltd.

Predicting Brook Trout occurrence in stream reaches throughout their native range in the eastern United States

USGS Publications Warehouse

DeWeber, Jefferson Tyrell; Wagner, Tyler

2015-01-01

The Brook Trout Salvelinus fontinalis is an important species of conservation concern in the eastern USA. We developed a model to predict Brook Trout population status within individual stream reaches throughout the species’ native range in the eastern USA. We utilized hierarchical logistic regression with Bayesian estimation to predict Brook Trout occurrence probability, and we allowed slopes and intercepts to vary among ecological drainage units (EDUs). Model performance was similar for 7,327 training samples and 1,832 validation samples based on the area under the receiver operating curve (∼0.78) and Cohen's kappa statistic (0.44). Predicted water temperature had a strong negative effect on Brook Trout occurrence probability at the stream reach scale and was also negatively associated with the EDU average probability of Brook Trout occurrence (i.e., EDU-specific intercepts). The effect of soil permeability was positive but decreased as EDU mean soil permeability increased. Brook Trout were less likely to occur in stream reaches surrounded by agricultural or developed land cover, and an interaction suggested that agricultural land cover also resulted in an increased sensitivity to water temperature. Our model provides a further understanding of how Brook Trout are shaped by habitat characteristics in the region and yields maps of stream-reach-scale predictions, which together can be used to support ongoing conservation and management efforts. These decision support tools can be used to identify the extent of potentially suitable habitat, estimate historic habitat losses, and prioritize conservation efforts by selecting suitable stream reaches for a given action. Future work could extend the model to account for additional landscape or habitat characteristics, include biotic interactions, or estimate potential Brook Trout responses to climate and land use changes.

Mapping the Potential for Eolian Surface Activity in Grasslands of the High Plains using Landsat Images

NASA Technical Reports Server (NTRS)

Gutmann, Ethan Dain

2002-01-01

There are over 100,000 square kilometers of eolian sand dunes and sand sheets in the High Plains of the central United States. These land-forms may be unstable and may reactivate again as a result of land-use, climate change, or natural climatic variability. The main goal of this thesis was to develop a model that could be used to map an estimate of future dune activity. Multi-temporal calibrated Landsats 5 Thematic Mapper (TM) and 7 Enhanced Thematic Map per Plus (ETM+) NDVI imagery were used in conjunction with the CENTURY vegetation model to correlate vegetation cover to climatic variability. This allows the creation of a predicted vegetation map which, combined with current wind and soil data, was used to create a potential sand transport map for range land in the High Plains under drought conditions.

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)

1992-01-01

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Integrated Assessment of Climate Change, Agricultural Land Use, and Regional Carbon Changes

NASA Astrophysics Data System (ADS)

MU, J.

2014-12-01

Changes in land use have caused a net release of carbon to the atmosphere over the last centuries and decades1. On one hand, agriculture accounts for 52% and 84% of global anthropogenic methane and nitrous oxide emissions, respectively. On the other hand, many agricultural practices can potentially mitigate greenhouse gas (GHG) emissions, the most prominent of which are improved cropland and grazing land management2. From this perspective, land use change that reduces emissions and/or increases carbon sequestration can play an important role in climate change mitigation. As shown in Figure 1, this paper is an integrated study of climate impacts, land uses, and regional carbon changes to examine, link and assess climate impacts on regional carbon changes via impacts on land uses. This study will contribute to previous research in two aspects: impacts of climate change on future land uses under an uncertain future world and projections of regional carbon dynamics due to changes in future land use. Specifically, we will examine how land use change under historical climate change using observed data and then project changes in land use under future climate projections from 14 Global Climate Models (GCMs) for two emission scenarios (i.e., RCP4.5 and RCP8.5). More importantly, we will investigate future land use under uncertainties with changes in agricultural development and social-economic conditions along with a changing climate. By doing this, we then could integrate with existing efforts by USGS land-change scientists developing and parameterizing models capable of projecting changes across a full spectrum of land use and land cover changes and track the consequences on ecosystem carbon to provide better information for land managers and policy makers when informing climate change adaptation and mitigation policies.

Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios

USGS Publications Warehouse

Wilson, Tamara; Sleeter, Benjamin M.; Sherba, Jason T.; Dick Cameron,

2015-01-01

Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km2) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km2 of land area within 10 km of a protected area boundary and over 18,000 km2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.

Coupling fast all-season soil strength land surface model with weather research and forecasting model to assess low-level icing in complex terrain

NASA Astrophysics Data System (ADS)

Sines, Taleena R.

Icing poses as a severe hazard to aircraft safety with financial resources and even human lives hanging in the balance when the decision to ground a flight must be made. When analyzing the effects of ice on aviation, a chief cause for danger is the disruption of smooth airflow, which increases the drag force on the aircraft therefore decreasing its ability to create lift. The Weather Research and Forecast (WRF) model Advanced Research WRF (WRF-ARW) is a collaboratively created, flexible model designed to run on distributed computing systems for a variety of applications including forecasting research, parameterization research, and real-time numerical weather prediction. Land-surface models, one of the physics options available in the WRF-ARW, output surface heat and moisture flux given radiation, precipitation, and surface properties such as soil type. The Fast All-Season Soil STrength (FASST) land-surface model was developed by the U.S. Army ERDC-CRREL in Hanover, New Hampshire. Designed to use both meteorological and terrain data, the model calculates heat and moisture within the surface layer as well as the exchange of these parameters between the soil, surface elements (such as snow and vegetation), and atmosphere. Focusing on the Presidential Mountain Range of New Hampshire under the NASA Experimental Program to Stimulate Competitive Research (EPSCoR) Icing Assessments in Cold and Alpine Environments project, one of the main goals is to create a customized, high resolution model to predict and assess ice accretion in complex terrain. The purpose of this research is to couple the FASST land-surface model with the WRF to improve icing forecasts in complex terrain. Coupling FASST with the WRF-ARW may improve icing forecasts because of its sophisticated approach to handling processes such as meltwater, freezing, thawing, and others that would affect the water and energy budget and in turn affect icing forecasts. Several transformations had to take place in order for the FASST land-surface model and WRF-ARW to work together as fully coupled models. Changes had to be made to the WRF-ARW build mechanisms (Chapter 1, section a) so that FASST would be recognized as a new option that could be chosen through the namelist and compiled with other modules. Similarly, FASST had to be altered to no longer read meteorological data from a file, but accept input from WRF-ARW at each time step in a way that did not alter the integrity or run-time processes of the model. Several icing events were available to test the newly coupled model as well as the performance of other available land-surface models from the WRF-ARW. A variation of event intensities and durations from these events were chosen to give a broader view of the land-surface models' abilities to accurately predict icing in complex terrain. Non- icing events were also used in testing to ensure the land-surface models were not predicting ice in the events where none occurred. When compared to the other land-surface models and observations FASST showed a warm bias in several regions. As the forecasts progressed, FASST appeared to attempt to correct this bias and performed similarly to the other land-surface models and at times better than these land-surface models in areas of the domain not affected by this bias. To correct this warm bias, future investigation should be conducted into the reasoning behind this warm bias, including but not limited to: FASST operation and elevation modeling, WRF-ARW variables and forecasting methods, as well as allowing for spin-up prior to forecast times. Following the correction to the warm bias, FASST can be parallelized to allow for operational forecast performance and included in the WRF-ARW forecasting suite for future software releases. (Abstract shortened by UMI.).

A new approach to complete aircraft landing gear noise prediction

NASA Astrophysics Data System (ADS)

Lopes, Leonard V.

This thesis describes a new landing gear noise prediction system developed at The Pennsylvania State University, called Landing Gear Model and Acoustic Prediction code (LGMAP). LGMAP is used to predict the noise of an isolated or installed landing gear geometry. The predictions include several techniques to approximate the aeroacoustic and aerodynamic interactions of landing gear noise generation. These include (1) a method for approximating the shielding of noise caused by the landing gear geometry, (2) accounting for local flow variations due to the wing geometry, (3) the interaction of the landing gear wake with high-lift devices, and (4) a method for estimating the effect of gross landing gear design changes on local flow and acoustic radiation. The LGMAP aeroacoustic prediction system has been created to predict the noise generated by a given landing gear. The landing gear is modeled as a set of simple components that represent individual parts of the structure. Each component, ranging from large to small, is represented by a simple geometric shape and the unsteady flow on the component is modeled based on an individual characteristic length, local flow velocity, and the turbulent flow environment. A small set of universal models is developed and applied to a large range of similar components. These universal models, combined with the actual component geometry and local environment, give a unique loading spectrum and acoustic field for each component. Then, the sum of all the individual components in the complete configuration is used to model the high level of geometric complexity typical of current aircraft undercarriage designs. A line of sight shielding algorithm based on scattering by a two-dimensional cylinder approximates the effect of acoustic shielding caused by the landing gear. Using the scattering from a cylinder in two-dimensions at an observer position directly behind the cylinder, LGMAP is able to estimate the reduction in noise due to shielding by the landing gear geometry. This thesis compares predictions with data from a recent wind tunnel experiment conducted at NASA Langley Research Center, and demonstrates that including the acoustic scattering can improve the predictions by LGMAP at all observer positions. In this way, LGMAP provides more information about the actual noise propagation than simple empirical schemes. Two-dimensional FLUENT calculations of approximate wing cross-sections are used by LGMAP to compute the change in noise due to the change in local flow velocity in the vicinity of the landing gear due to circulation around the wing. By varying angle of attack and flap deflection angle in the CFD calculations, LGMAP is able to predict the noise level change due to the change in local flow velocity in the landing gear vicinity. A brief trade study is performed on the angle of attack of the wing and flap deflection angle of the flap system. It is shown that increasing the angle of attack or flap deflection angle reduces the flow velocity in the vicinity of the landing gear, and therefore the predicted noise. Predictions demonstrate the ability of the prediction system to quickly estimate the change in landing gear noise caused by a change in wing configuration. A three-dimensional immersed boundary CFD calculation of simplified landing gear geometries provides relatively quick estimates of the mean flow around the landing gear. The mean flow calculation provides the landing gear wake geometry for the prediction of trailing edge noise associated with the interaction of the landing gear wake with the high lift devices. Using wind tunnel experiments that relate turbulent intensity to wake size and the Ffowcs Williams and Hall trailing edge noise equation for the acoustic calculation, LGMAP is able to predict the landing gear wake generated trailing edge noise. In this manner, LGMAP includes the effect of the interaction of the landing gear's wake with the wing/flap system on the radiated noise. The final prediction technique implemented includes local flow calculations of a landing gear with various truck angles using the immersed boundary scheme. Using the mean flow calculation, LGMAP is able to predict noise changes caused by gross changes in landing gear design. Calculations of the mean flow around the landing gear show that the rear wheels of a six-wheel bogie experience significantly reduced mean flow velocity when the truck is placed in a toe-down configuration. This reduction in the mean flow results is a lower noise signature from the rear wheel. Since the noise from a six-wheel bogie at flyover observer positions is primarily composed of wheel noise, the reduced local flow velocity results in a reduced noise signature from the entire landing gear geometry. Comparisons with measurements show the accuracy of the predictions of landing gear noise levels and directivity. Airframe noise predictions for the landing gear of a complete aircraft are described including all of the above mentioned developments and prediction techniques. These show that the nose gear noise and the landing gear wake/flap interaction noise, while not significantly changing the overall shape of the radiated noise, do contribute to the overall noise from the installed landing gear.

Prediction of Landing Gear Noise Reduction and Comparison to Measurements

NASA Technical Reports Server (NTRS)

Lopes, Leonard V.

2010-01-01

Noise continues to be an ongoing problem for existing aircraft in flight and is projected to be a concern for next generation designs. During landing, when the engines are operating at reduced power, the noise from the airframe, of which landing gear noise is an important part, is equal to the engine noise. There are several methods of predicting landing gear noise, but none have been applied to predict the change in noise due to a change in landing gear design. The current effort uses the Landing Gear Model and Acoustic Prediction (LGMAP) code, developed at The Pennsylvania State University to predict the noise from landing gear. These predictions include the influence of noise reduction concepts on the landing gear noise. LGMAP is compared to wind tunnel experiments of a 6.3%-scale Boeing 777 main gear performed in the Quiet Flow Facility (QFF) at NASA Langley. The geometries tested in the QFF include the landing gear with and without a toboggan fairing and the door. It is shown that LGMAP is able to predict the noise directives and spectra from the model-scale test for the baseline configuration as accurately as current gear prediction methods. However, LGMAP is also able to predict the difference in noise caused by the toboggan fairing and by removing the landing gear door. LGMAP is also compared to far-field ground-based flush-mounted microphone measurements from the 2005 Quiet Technology Demonstrator 2 (QTD 2) flight test. These comparisons include a Boeing 777-300ER with and without a toboggan fairing that demonstrate that LGMAP can be applied to full-scale flyover measurements. LGMAP predictions of the noise generated by the nose gear on the main gear measurements are also shown.

Application of Maxent Multivariate Analysis to Define Climate-Change Effects on Species Distributions and Changes

DTIC Science & Technology

2014-09-01

approaches. Ecological Modelling Volume 200, Issues 1–2, 10, pp 1–19. Buhlmann, Kurt A ., Thomas S.B. Akre , John B. Iverson, Deno Karapatakis, Russell A ...statistical multivariate analysis to define the current and projected future range probability for species of interest to Army land managers. A software...15 Figure 4. RCW omission rate and predicted area as a function of the cumulative threshold

Change We Can Fight Over: The Relationship between Arable Land Supply and Substate Conflict

DTIC Science & Technology

2010-01-01

environmental impact of global warming has spurred a parallel discussion among national security academics and policymakers about the security...consequences of climate change. Roughly speaking, there are two camps in this discussion -one that ominously predicts the potential for global warming to spark...future climate change, but the stark reality is that global warming is already upon us. Thus, policymakers need to know -both now and in the coming

Preliminary Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M.; Grant, J.; Parker, T.; Crisp, J.; Squyres, S.; Carr, M.; Haldemann, A.; Arvidson, R.; Ehlmann, B.; Bell, J.

2004-01-01

Selection of the Mars Exploration Rover (MER) landing sites took place over a three year period in which engineering constraints were identified, 155 possible sites were downselected to the final two, surface environments and safety considerations were developed, and the potential science return at the sites was considered. Landing sites in Gusev crater and Meridiani Planum were selected because they appeared acceptably safe for MER landing and roving and had strong morphologic and mineralogical indicators of liquid water in their past and thus appeared capable of addressing the science objectives of the MER missions, which are to determine the aqueous, climatic, and geologic history of sites on Mars where conditions may have been favorable to the preservation of evidence of possible pre-biotic or biotic processes. Engineering constraints important to the selection included: latitude (10 N-15 S) for maximum solar power; elevation (<-1.3 km) for sufficient atmosphere to slow the lander; low horizontal winds, shear and turbulence in the last few kilometers to minimize horizontal velocity; low 10-m scale slopes to reduce airbag spinup and bounce; moderate rock abundance to reduce abrasion or stroke-out of the airbags; and a radar-reflective, load-bearing and trafficable surface safe for landing and roving that is not dominated by fine-grained dust. In selecting the MER landing sites these engineering constraints were addressed via comprehensive evaluation of surface and atmospheric characteristics from existing remote sensing data and models as well as targeted orbital information acquired from Mars Global Surveyor and Mars Odyssey. This evaluation resulted in a number of predictions of the surface characteristics of the sites, which are tested in this abstract. Relating remote sensing signatures to surface characteristics at landing sites allows these sites to be used as ground truth for the orbital data, is essential for selecting and validating landing sites for future missions, and is required for correctly interpreting the surfaces and materials globally present on Mars.

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

2016-01-01

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

Simulating carbon sequestration using cellular automata and land use assessment for Karaj, Iran

NASA Astrophysics Data System (ADS)

Khatibi, Ali; Pourebrahim, Sharareh; Mokhtar, Mazlin Bin

2018-06-01

Carbon sequestration has been proposed as a means of slowing the atmospheric and marine accumulation of greenhouse gases. This study used observed and simulated land use/cover changes to investigate and predict carbon sequestration rates in the city of Karaj. Karaj, a metropolis of Iran, has undergone rapid population expansion and associated changes in recent years, and these changes make it suitable for use as a case study for rapidly expanding urban areas. In particular, high quality agricultural space, green space and gardens have rapidly transformed into industrial, residential and urban service areas. Five classes of land use/cover (residential, agricultural, rangeland, forest and barren areas) were considered in the study; vegetation and soil samples were taken from 20 randomly selected locations. The level of carbon sequestration was determined for the vegetation samples by calculating the amount of organic carbon present using the dry plant weight method, and for soil samples by using the method of Walkley and Black. For each area class, average values of carbon sequestration in vegetation and soil samples were calculated to give a carbon sequestration index. A cellular automata approach was used to simulate changes in the classes. Finally, the carbon sequestration indices were combined with simulation results to calculate changes in carbon sequestration for each class. It is predicted that, in the 15 year period from 2014 to 2029, much agricultural land will be transformed into residential land, resulting in a severe reduction in the level of carbon sequestration. Results from this study indicate that expansion of forest areas in urban counties would be an effective means of increasing the levels of carbon sequestration. Finally, future opportunities to include carbon sequestration into the simulation of land use/cover changes are outlined.

A new framework for modeling urban land expansion in peri-urban area by combining multi-source datasets and data assimilation

NASA Astrophysics Data System (ADS)

Zhang, Z.; Xiao, R.; Li, X.

2015-12-01

Peri-urban area is a new type region under the impacts of both rural Industrialization and the radiation of metropolitan during rapid urbanization. Due to its complex natural and social characteristics and unique development patterns, many problems such as environmental pollution and land use waste emerged, which became an urgent issue to be addressed. Study area in this paper covers three typical peri-urban districts (Pudong, Fengxian and Jinshan), which around the Shanghai inner city. By coupling cellular automata and multi-agent system model as the basic tools, this research focus on modelling the urban land expansion and driving mechanism in peri-urban area. The big data is aslo combined with the Bayesian maximum entropy method (BME) for spatiotemporal prediction of multi-source data, which expand the dataset of urban expansion models. Data assimilation method is used to optimize the parameters of the coupling model and minimize the uncertainty of observations, improving the precision of future simulation in peri-urban area. By setting quantitative parameters, the coupling model can effectively improve the simulation of the process of urban land expansion under different policies and management schemes, in order to provide scientificimplications for new urbanization strategy. In this research, we precise the urban land expansion simulation and prediction for peri-urban area, expand the scopes and selections of data acquisition measurements and methods, develop the new applications of the data assimilation method in geographical science, provide a new idea for understanding the inherent rules of urban land expansion, and give theoretical and practical support for the peri-urban area in urban planning and decision making.

Towards an integrated set of surface meterological observations for climate science and applications

NASA Astrophysics Data System (ADS)

Dunn, Robert; Thorne, Peter

2017-04-01

We cannot predict what is not observed, and we cannot analyse what is not archived. To meet current scientific and societal demands, as well as future requirements for climate services, it is vital that the management and curation of land-based meteorological data holdings is improved. A comprehensive global set of data holdings, of known provenance, integrated across both climate variable and timescale are required to meet the wide range of user needs. Presently, the land-based holdings are highly fractured into global, region and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. We present a high level overview, based on broad community input, of the steps that are required to bring about this integration and progress towards such a database. Any long-term, international, program creating such an integrated database will transform the our collective ability to provide societally relevant research, analysis and predictions across the globe.

Oil and gas development footprint in the Piceance Basin, western Colorado

USGS Publications Warehouse

Martinez, Cericia D.; Preston, Todd M.

2018-01-01

Understanding long-term implications of energy development on ecosystem functionrequires establishing regional datasets to quantify past development and determine relationships to predict future development. The Piceance Basin in western Colorado has a history of energy production and development is expected to continue into the foreseeable future due to abundant natural gas resources. To facilitate analyses of regional energy development we digitized all well pads in the Colorado portion of the basin, determined the previous land cover of areas converted to well pads over three time periods (2002–2006, 2007–2011, and 2012–2016), and explored the relationship between number of wells per pad and pad area to model future development. We also calculated the area of pads constructed prior to 2002. Over 21 million m2 has been converted to well pads with approximately 13 million m2 converted since 2002. The largest land conversion since 2002 occurred in shrub/scrub (7.9 million m2), evergreen (2.1 million m2), and deciduous (1.3 million m2) forest environments based on National Land Cover Database classifications. Operational practices have transitioned from single well pads to multi-well pads, increasing the average number of wells per pad from 2.5 prior to 2002, to 9.1 between 2012 and 2016. During the same time period the pad area per well has increased from 2030 m2 to 3504 m2. Kernel density estimation was used to model the relationship between the number of wells per pad and pad area, with these curves exhibiting a lognormal distribution. Therefore, either kernel density estimation or lognormal probability distributions may potentially be used to model land use requirements for future development. Digitized well pad locations in the Piceance Basin contribute to a growing body of spatial data on energy infrastructure and, coupled with study results, will facilitate future regional and national studies assessing the spatial and temporal effects of energy development on ecosystem function.

Land-cover changes predict steep declines for the Sumatran orangutan (Pongo abelii)

PubMed Central

Wich, Serge A.; Singleton, Ian; Nowak, Matthew G.; Utami Atmoko, Sri Suci; Nisam, Gonda; Arif, Sugesti Mhd.; Putra, Rudi H.; Ardi, Rio; Fredriksson, Gabriella; Usher, Graham; Gaveau, David L. A.; Kühl, Hjalmar S.

2016-01-01

Positive news about Sumatran orangutans is rare. The species is critically endangered because of forest loss and poaching, and therefore, determining the impact of future land-use change on this species is important. To date, the total Sumatran orangutan population has been estimated at 6600 individuals. On the basis of new transect surveys, we estimate a population of 14,613 in 2015. This higher estimate is due to three factors. First, orangutans were found at higher elevations, elevations previously considered outside of their range and, consequently, not surveyed previously. Second, orangutans were found more widely distributed in logged forests. Third, orangutans were found in areas west of the Toba Lake that were not previously surveyed. This increase in numbers is therefore due to a more wide-ranging survey effort and is not indicative of an increase in the orangutan population in Sumatra. There are evidently more Sumatran orangutans remaining in the wild than we thought, but the species remains under serious threat. Current scenarios for future forest loss predict that as many as 4500 individuals could vanish by 2030. Despite the positive finding that the population is double the size previously estimated, our results indicate that future deforestation will continue to be the cause of rapid declines in orangutan numbers. Hence, we urge that all developmental planning involving forest loss be accompanied by appropriate environmental impact assessments conforming with the current national and provincial legislations, and, through these, implement specific measures to reduce or, better, avoid negative impacts on forests where orangutans occur. PMID:26973868

Land-cover changes predict steep declines for the Sumatran orangutan (Pongo abelii).

PubMed

Wich, Serge A; Singleton, Ian; Nowak, Matthew G; Utami Atmoko, Sri Suci; Nisam, Gonda; Arif, Sugesti Mhd; Putra, Rudi H; Ardi, Rio; Fredriksson, Gabriella; Usher, Graham; Gaveau, David L A; Kühl, Hjalmar S

2016-03-01

Positive news about Sumatran orangutans is rare. The species is critically endangered because of forest loss and poaching, and therefore, determining the impact of future land-use change on this species is important. To date, the total Sumatran orangutan population has been estimated at 6600 individuals. On the basis of new transect surveys, we estimate a population of 14,613 in 2015. This higher estimate is due to three factors. First, orangutans were found at higher elevations, elevations previously considered outside of their range and, consequently, not surveyed previously. Second, orangutans were found more widely distributed in logged forests. Third, orangutans were found in areas west of the Toba Lake that were not previously surveyed. This increase in numbers is therefore due to a more wide-ranging survey effort and is not indicative of an increase in the orangutan population in Sumatra. There are evidently more Sumatran orangutans remaining in the wild than we thought, but the species remains under serious threat. Current scenarios for future forest loss predict that as many as 4500 individuals could vanish by 2030. Despite the positive finding that the population is double the size previously estimated, our results indicate that future deforestation will continue to be the cause of rapid declines in orangutan numbers. Hence, we urge that all developmental planning involving forest loss be accompanied by appropriate environmental impact assessments conforming with the current national and provincial legislations, and, through these, implement specific measures to reduce or, better, avoid negative impacts on forests where orangutans occur.

Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production.

PubMed

Fodor, Nándor; Challinor, Andrew; Droutsas, Ioannis; Ramirez-Villegas, Julian; Zabel, Florian; Koehler, Ann-Kristin; Foyer, Christine H

2017-11-01

Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. When CO2 fertilization effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarize the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

Land Use/land Cover Changes in Semi-Arid Mountain Landscape in Southern India: a Geoinformatics Based Markov Chain Approach

NASA Astrophysics Data System (ADS)

Rahaman, S. A.; Aruchamy, S.; Balasubramani, K.; Jegankumar, R.

2017-05-01

Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

Exploring eco-hydrological consequences of the Amazonian ecosystems under climate and land-use changes in the 21st century

NASA Astrophysics Data System (ADS)

Zhang, K.; Castanho, A. D.; Moghim, S.; Bras, R. L.; Coe, M. T.; Costa, M. H.; Levine, N. M.; Longo, M.; McKnight, S.; Wang, J.; Moorcroft, P. R.

2012-12-01

Deforestation and drought have imposed regional-scale perturbations onto Amazonian ecosystems and are predicted to cause larger negative impacts on the Amazonian ecosystems and associated regional carbon dynamics in the 21st century. However, global climate models (GCMs) vary greatly in their projections of future climate change in Amazonia, giving rise to uncertainty in the expected fate of the Amazon over the coming century. In this study, we explore the possible eco-hydrological consequences of the Amazonian ecosystems under projected climate and land-use changes in the 21st century using two state-of-the-art terrestrial ecosystem models—Ecosystem Demography Model 2.1(ED2.1) and Integrated Biosphere Simulator model (IBIS)—driven by three representative, bias-corrected climate projections from three IPCC GCMs (NCARPCM1, NCARCCSM3 and HadCM3), coupled with two land-use change scenarios (a business-as-usual and a strict governance scenario). We also analyze the relative roles of climate change, CO2 fertilization, land-use change and fire in driving the projected composition and structure of the Amazonian ecosystems. Our results show that CO2 fertilization enhances vegetation productivity and above-ground biomass (AGB) in the region, while land-use change and fire cause AGB loss and the replacement of forests by the savanna-like vegetation. The impacts of climate change depend strongly on the direction and severity of projected precipitation changes in the region. In particular, when intensified water stress is superimposed on unregulated deforestation, both ecosystem models predict large-scale dieback of Amazonian rainforests.

Global Demand for Natural Resources Eliminated More Than 100,000 Bornean Orangutans.

PubMed

Voigt, Maria; Wich, Serge A; Ancrenaz, Marc; Meijaard, Erik; Abram, Nicola; Banes, Graham L; Campbell-Smith, Gail; d'Arcy, Laura J; Delgado, Roberto A; Erman, Andi; Gaveau, David; Goossens, Benoit; Heinicke, Stefanie; Houghton, Max; Husson, Simon J; Leiman, Ashley; Sanchez, Karmele Llano; Makinuddin, Niel; Marshall, Andrew J; Meididit, Ari; Miettinen, Jukka; Mundry, Roger; Musnanda; Nardiyono; Nurcahyo, Anton; Odom, Kisar; Panda, Adventus; Prasetyo, Didik; Priadjati, Aldrianto; Purnomo; Rafiastanto, Andjar; Russon, Anne E; Santika, Truly; Sihite, Jamartin; Spehar, Stephanie; Struebig, Matthew; Sulbaran-Romero, Enrique; Tjiu, Albertus; Wells, Jessie; Wilson, Kerrie A; Kühl, Hjalmar S

2018-03-05

Unsustainable exploitation of natural resources is increasingly affecting the highly biodiverse tropics [1, 2]. Although rapid developments in remote sensing technology have permitted more precise estimates of land-cover change over large spatial scales [3-5], our knowledge about the effects of these changes on wildlife is much more sparse [6, 7]. Here we use field survey data, predictive density distribution modeling, and remote sensing to investigate the impact of resource use and land-use changes on the density distribution of Bornean orangutans (Pongo pygmaeus). Our models indicate that between 1999 and 2015, half of the orangutan population was affected by logging, deforestation, or industrialized plantations. Although land clearance caused the most dramatic rates of decline, it accounted for only a small proportion of the total loss. A much larger number of orangutans were lost in selectively logged and primary forests, where rates of decline were less precipitous, but where far more orangutans are found. This suggests that further drivers, independent of land-use change, contribute to orangutan loss. This finding is consistent with studies reporting hunting as a major cause in orangutan decline [8-10]. Our predictions of orangutan abundance loss across Borneo suggest that the population decreased by more than 100,000 individuals, corroborating recent estimates of decline [11]. Practical solutions to prevent future orangutan decline can only be realized by addressing its complex causes in a holistic manner across political and societal sectors, such as in land-use planning, resource exploitation, infrastructure development, and education, and by increasing long-term sustainability [12]. VIDEO ABSTRACT. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluating hydrological response of future land cover change scenarios in the San Pedro river (U.S./Mexico) with the Automated Geospatial Watershed (AGWA) tool

USDA-ARS?s Scientific Manuscript database

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed to characterize potential hydrologic impacts from future urban growth through time. Fu...

Evaluating Hydrological Response of Future Land Cover Change Scenarios in the San Pedro River (U.S./Mexico) with the Automated Geospatial Watershed Assessment (AGWA) Tool.

EPA Science Inventory

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed to characterize potential hydrologic impacts from future urban gro...

Unravelling the structure of species extinction risk for predictive conservation science.

PubMed

Lee, Tien Ming; Jetz, Walter

2011-05-07

Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha-1 h-1 yr-1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

PubMed

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha -1  h -1  yr -1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang

2012-01-01

The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Connecting differential responses of native and invasive riparian plants to climate change and environmental alteration.

PubMed

Flanagan, Neal E; Richardson, Curtis J; Ho, Mengchi

2015-04-01

Climate change is predicted to impact river systems in the southeastern United States through alterations of temperature, patterns of precipitation and hydrology. Future climate scenarios for the southeastern United States predict (1) surface water temperatures will warm in concert with air temperature, (2) storm flows will increase and base flows will decrease, and (3) the annual pattern of synchronization between hydroperiod and water temperature will be altered. These alterations are expected to disturb floodplain plant communities, making them more vulnerable to establishment of invasive species. The primary objective of this study is to evaluate whether native and invasive riparian plant assemblages respond differently to alterations of climate and land use. To study the response of riparian wetlands to watershed and climate alterations, we utilized an existing natural experiment imbedded in gradients of temperature and hydrology-found among dammed and undammed rivers. We evaluated a suite of environmental variables related to water temperature, hydrology, watershed disturbance, and edaphic conditions to identify the strongest predictors of native and invasive species abundances. We found that native species abundance is strongly influenced by climate-driven variables such as temperature and hydrology, while invasive species abundance is more strongly influenced by site-specific factors such as land use and soil nutrient availability. The patterns of synchronization between plant phenology, annual hydrographs, and annual water temperature cycles may be key factors sustaining the viability of native riparian plant communities. Our results demonstrate the need to understand the interactions between climate, land use, and nutrient management in maintaining the species diversity of riparian plant communities. Future climate change is likely to result in diminished competitiveness of native plant species, while the competitiveness of invasive species will increase due to anthropogenic watershed disturbance and accelerated nutrient and sediment export.

Research plan for lands administered by the U.S. Department of the Interior in the Interior Columbia Basin and Snake River Plateau

USGS Publications Warehouse

Beever, Erik A.; Pyke, David A.

2002-01-01

The research strategy focuses on disturbance processes and events that have been the primary drivers of change, to provide a predictive model for future changes. These drivers include fire, nonnative plants, herbivory, roads and associated human influences, and climate change. Whereas management in the western United States has striven to move from an inefficient species-based approach to a habitat-based approach, the plan focuses on ecosystem function and ecological processes as critical measures of habitat response. Because of the large amount and contiguity of public lands in the western United States, the region presents both a compelling opportunity to implement landscape-level science and a challenge to underst

Modification of land-atmosphere interactions by CO2 effects

NASA Astrophysics Data System (ADS)

Lemordant, Leo; Gentine, Pierre

2017-04-01

Plant stomata couple the energy, water and carbon cycles. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the impact of potential heat waves. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels, and of the coupling between the carbon and water cycles are therefore critical to forecasting seasonal climate, water cycle dynamics and to enhance the accuracy of extreme event prediction under future climate.

Earth land landing alternatives: Lunar transportation system

NASA Technical Reports Server (NTRS)

Meyerson, Robert

1992-01-01

The objectives of this study are as follows: (1) develop a landing option such that it is a viable trade option for future NASA missions; (2) provide NASA programs with solid technical support in the landing systems area; (3) develop the technical staff; and (4) advance the state of landing systems technology to apply to future NASA missions. All results are presented in viewgraph format.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

USGS Publications Warehouse

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.

Historical Pattern and Future Trajectories of Terrestrial N2O Emission driven by Multi-factor Global Changes

NASA Astrophysics Data System (ADS)

Lu, C.; Tian, H.; Yang, J.; Zhang, B.; Xu, R.

2015-12-01

Nitrous oxide (N2O) is among the most important greenhouse gases only next to carbon dioxide (CO2) and methane (CH4) due to its long life time and high radiative forcing (with a global warming potential 265 times as much as CO2 at 100-year time horizon). The Atmospheric concentration of N2O has increased by 20% since pre-industrial era, and this increase plays a significant role in shaping anthropogenic climate change. However, compared to CO2- and CH4-related research, fewer studies have been performed in assessing and predicting the spatiotemporal patterns of N2O emission from natural and agricultural soils. Here we used a coupled biogeochemical model, DLEM, to quantify the historical and future changes in global terrestrial N2O emissions resulting from natural and anthropogenic perturbations including climate variability, atmospheric CO2 concentration, nitrogen deposition, land use and land cover changes, and agricultural land management practices (i.e., synthetic nitrogen fertilizer use, manure application, and irrigation etc.) over the period 1900-2099. We focused on inter-annual variation and long-term trend of terrestrial N2O emission driven by individual and combined environmental changes during historical and future periods. The sensitivity of N2O emission to climate, atmospheric composition, and human activities has been examined at biome-, latitudinal, continental and global scales. Future projections were conducted to identify the hot spots and hot time periods of global N2O emission under two emission scenarios (RCP2.6 and RCP8.5). It provides a modeling perspective for understanding human-induced N2O emission growth and developing potential management strategies to mitigate further atmospheric N2O increase and climate warming.

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

PubMed Central

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. PMID:25372571

Spatial allocation of future landscape patterns for biomass and alleviation of hydrologic impacts of climate change

NASA Astrophysics Data System (ADS)

Ssegane, H.; Negri, M. C.

2015-12-01

Current and future demand for food, feed, fiber, and energy require novel approaches to land management, which demands that multifunctional landscapes are created to integrate various ecosystem functions into a sustainable land use. Concurrently, the Intergovernmental Panel on Climate Change (IPCC) predicts an increase of 2 to 4°C over the next 100 years above the preindustrial baseline, beginning as early as 2016 to 2035 over all seasons in the North America. This climate change is projected to further strain water resources currently stressed by anthropogenic activities. Therefore, placement of bioenergy crops on strategically selected sub-field areas in an agricultural landscape has the potential to increase the environmental and economic sustainability if location and choice of the crops result in minimal disruption of current food production systems and therefore cause minimal indirect land use change. This study identified sub-field marginal areas in an agricultural watershed using soil-based environmental sustainability criteria and a crop productivity index. Future landscape patterns (FLPs) were developed by allocating bioenergy crops (switchgrass: Panicum virgatum or shrub willows: Salix spp.) to these marginal areas (20% of the watershed). SWAT hydrologic model and dynamically downscaled climatic projection were used to asses impact of climate change on extreme flow conditions, total annual production of commodity and bioenergy crops, and water quality under current and future landscape patterns for the mid-21st century (2045-2055) and late 21st century (2085-2095) climatic projections. The frequency of flood and drought conditions was projected to increase while the corresponding durations to decrease. Sediment yields were projected to increase by 85% to 170% while FLPs would mitigate this increase by 26% to 32%.

Increasing Understanding of Public Problems and Policies, 1997.

ERIC Educational Resources Information Center

Ernstes, David P., Ed.; Hicks, Dawne M., Ed.

This document contains 21 papers: "Land Grant University and Extension in the 21st Century" (Jon Wefald); "A Reality Check" (Bud Webb); "Land Grant Colleges and Universities of the Future" (Michael J. Phillips); "Vulnerability of the Land Grant Colleges of Agriculture: A Public Affairs Perspective" (Allen Rosenfeld); "The Future of Land Grant…

A cost-effectiveness analysis of water security and water quality: impacts of climate and land-use change on the River Thames system.

PubMed

Whitehead, P G; Crossman, J; Balana, B B; Futter, M N; Comber, S; Jin, L; Skuras, D; Wade, A J; Bowes, M J; Read, D S

2013-11-13

The catchment of the River Thames, the principal river system in southern England, provides the main water supply for London but is highly vulnerable to changes in climate, land use and population. The river is eutrophic with significant algal blooms with phosphorus assumed to be the primary chemical indicator of ecosystem health. In the Thames Basin, phosphorus is available from point sources such as wastewater treatment plants and from diffuse sources such as agriculture. In order to predict vulnerability to future change, the integrated catchments model for phosphorus (INCA-P) has been applied to the river basin and used to assess the cost-effectiveness of a range of mitigation and adaptation strategies. It is shown that scenarios of future climate and land-use change will exacerbate the water quality problems, but a range of mitigation measures can improve the situation. A cost-effectiveness study has been undertaken to compare the economic benefits of each mitigation measure and to assess the phosphorus reductions achieved. The most effective strategy is to reduce fertilizer use by 20% together with the treatment of effluent to a high standard. Such measures will reduce the instream phosphorus concentrations to close to the EU Water Framework Directive target for the Thames.

Improving simulated long-term responses of vegetation to temperature and precipitation extremes using the ACME land model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Warren, J.; Guha, A.

2017-12-01

While carbon and energy fluxes in current Earth system models generally have reasonable instantaneous responses to extreme temperature and precipitation events, they often do not adequately represent the long-term impacts of these events. For example, simulated net primary productivity (NPP) may decrease during an extreme heat wave or drought, but may recover rapidly to pre-event levels following the conclusion of the extreme event. However, field measurements indicate that long-lasting damage to leaves and other plant components often occur, potentially affecting the carbon and energy balance for months after the extreme event. The duration and frequency of such extreme conditions is likely to shift in the future, and therefore it is critical for Earth system models to better represent these processes for more accurate predictions of future vegetation productivity and land-atmosphere feedbacks. Here we modify the structure of the Accelerated Climate Model for Energy (ACME) land surface model to represent long-term impacts and test the improved model against observations from experiments that applied extreme conditions in growth chambers. Additionally, we test the model against eddy covariance measurements that followed extreme conditions at selected locations in North America, and against satellite-measured vegetation indices following regional extreme events.

Research on the food security condition and food supply capacity of Egypt.

PubMed

Deng, Jian; Xiang, Youzhen; Hao, Wenhui; Feng, Yongzhong; Yang, Gaihe; Ren, Guangxin; Han, Xinhui

2014-01-01

Food security is chronically guaranteed in Egypt because of the food subsidy policy of the country. However, the increasing Egyptian population is straining the food supply. To study changes in Egyptian food security and future food supply capacity, we analysed the historical grain production, yield per unit, grain-cultivated area, and per capita grain possession of Egypt. The GM (1,1) model of the grey system was used to predict the future population. Thereafter, the result was combined with scenario analysis to forecast the grain possession and population carrying capacity of Egypt under different scenarios. Results show that the increasing population and limitations in cultivated land will strain Egyptian food security. Only in high cultivated areas and high grain yield scenarios before 2020, or in high cultivated areas and mid grain yield scenarios before 2015, can food supply be basically satisfied (assurance rate ≥ 80%) under a standard of 400 kg per capita. Population carrying capacity in 2030 is between 51.45 and 89.35 million. Thus, we propose the use of advanced technologies in agriculture and the adjustment of plant structure and cropping systems to improve land utilization efficiency. Furthermore, urbanization and other uses of cultivated land should be strictly controlled to ensure the planting of grains.

Xingu Project - Integrating Land Use Planning and Water Governance in Amazonia: Towards Improved Freshwater Security in the Agricultural Frontier of Mato Grosso.

NASA Astrophysics Data System (ADS)

Krusche, A. V.; Ballester, M. V.; Neill, C.; Elsenbeer, H.; Johnson, M. S.; Coe, M. T.; Garavello, M.; Molina, S. G.; Empinotti, V.; Reichardt, F.; Deegan, L.; Harris, L.

2014-12-01

The main goal of this project is to identify how impacts from land conversion, cropland expansion and intensification of both crop and animal production interact to affect regional evapotranspiration, rainfall generation, river flooding, and water quality and stream habitats, allowing us to identify thresholds of change that will endanger agricultural production, livelihoods of non-agricultural settlers and the region's new urban population and infrastructure. We will survey the effects of this on (1) soybean farmers, (2) cattle ranchers, (3) small-scale farm families, (4) rural non-agriculturists, including fishers, and (5) urban residents and map their roles as stakeholders. We will also conduct current water use surveys among the different stakeholder groups, accompanied by questions on desired aspects for future freshwater security to identify targets for desirable outcomes of water governance strategies. These targets, together with the information on land use drivers, water quantity and quality and predicted scenarios for global changes will be incorporated into a fully integrated and interactive geospatially oriented socio-ecological model that can serve as framework for future water governance that enhances Freshwater Security in such systems. This is an international cooperation initiative lead by Brazil and with the participation of Canada, Germany and United States of America.

Evidence of Microbial Regulation of Biogeochemical Cycles from a Study on Methane Flux and Land Use Change

PubMed Central

Nazaries, Loïc; Pan, Yao; Bodrossy, Levente; Baggs, Elizabeth M.; Millard, Peter; Murrell, J. Colin

2013-01-01

Microbes play an essential role in ecosystem functions, including carrying out biogeochemical cycles, but are currently considered a black box in predictive models and all global biodiversity debates. This is due to (i) perceived temporal and spatial variations in microbial communities and (ii) lack of ecological theory explaining how microbes regulate ecosystem functions. Providing evidence of the microbial regulation of biogeochemical cycles is key for predicting ecosystem functions, including greenhouse gas fluxes, under current and future climate scenarios. Using functional measures, stable-isotope probing, and molecular methods, we show that microbial (community diversity and function) response to land use change is stable over time. We investigated the change in net methane flux and associated microbial communities due to afforestation of bog, grassland, and moorland. Afforestation resulted in the stable and consistent enhancement in sink of atmospheric methane at all sites. This change in function was linked to a niche-specific separation of microbial communities (methanotrophs). The results suggest that ecological theories developed for macroecology may explain the microbial regulation of the methane cycle. Our findings provide support for the explicit consideration of microbial data in ecosystem/climate models to improve predictions of biogeochemical cycles. PMID:23624469

Numerical Study of the Effect of Urbanization on the Climate of Desert Cities

NASA Astrophysics Data System (ADS)

Kamal, Samy

This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For each city, the land-use maps of 1985 and 2010 from Landsat satellite observation, and a projected land-use map for 2030, are used to represent the past, present, and future. An additional set of simulations for Las Vegas, the largest of the five cities, uses the NLCD 1992 and 2006 land-use maps and an idealized historical land-use map with no urban coverage for 1900. The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization. The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.

Evaluating hydrological response of future land cover change scenarios in the San Pedro River (U.S./Mexico) with the automated geospatial watershed assessment (AGWA) tool

Treesearch

William G. Kepner; I. Shea Burns; David C Goodrich; D. Phillip Guertin; Gabriel S. Sidman; Lainie R. Levick; Wison W.S. Yee; Melissa M.A. Scianni; Clifton S. Meek; Jared B. Vollmer

2016-01-01

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed to characterize potential hydrologic impacts from future urban growth through time. Future growth is represented by housing density maps generated in decadal...

Representing winter wheat in the Community Land Model (version 4.5)

NASA Astrophysics Data System (ADS)

Lu, Yaqiong; Williams, Ian N.; Bagley, Justin E.; Torn, Margaret S.; Kueppers, Lara M.

2017-05-01

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

Modeling nitrate from land surface to wells' perforations under agricultural land: success, failure, and future scenarios in a Mediterranean case study

NASA Astrophysics Data System (ADS)

Levy, Yehuda; Shapira, Roi H.; Chefetz, Benny; Kurtzman, Daniel

2017-07-01

Contamination of groundwater resources by nitrate leaching under agricultural land is probably the most troublesome agriculture-related water contamination worldwide. Contaminated areas often show large spatial variability of nitrate concentration in wells. In this study, we tried to assess whether this spatial variability can be characterized on the basis of land use and standard agricultural practices. Deep soil sampling (10 m) was used to calibrate vertical flow and nitrogen-transport numerical models of the unsaturated zone under different agricultural land uses. Vegetable fields (potato and strawberry) and deciduous orchards (persimmon) in the Sharon area overlying the coastal aquifer of Israel were examined. Average nitrate-nitrogen fluxes below vegetable fields were 210-290 kg ha-1 yr-1 and under deciduous orchards were 110-140 kg ha-1 yr-1. The output water and nitrate-nitrogen fluxes of the unsaturated-zone models were used as input data for a three-dimensional flow and nitrate-transport model in the aquifer under an area of 13.3 km2 of agricultural land. The area was subdivided into four agricultural land uses: vegetables, deciduous orchards, citrus orchards, and non-cultivated. Fluxes of water and nitrate-nitrogen below citrus orchards were taken from a previous study in the area. The groundwater flow model was calibrated to well heads by changing the hydraulic conductivity. The nitrate-transport model, which was fed by the above-mentioned models of the unsaturated zone, succeeded in reconstructing the average nitrate concentration in the wells. However, this transport model failed in calculating the high concentrations in the most contaminated wells and the large spatial variability of nitrate concentrations in the aquifer. To reconstruct the spatial variability and enable predictions, nitrate fluxes from the unsaturated zone were multiplied by local multipliers. This action was rationalized by the fact that the high concentrations in some wells cannot be explained by regular agricultural activity and are probably due to malfunctions in the well area. Prediction of the nitrate concentration 40 years in the future with three nitrogen-fertilization scenarios showed that (i) under the business as usual fertilization scenario, the nitrate concentration (as NO3-) will increase on average by 19 mg L-1; (ii) under a scenario of 25 % reduction of nitrogen fertilization, the nitrate concentration in the aquifer will stabilize; (iii) with a 50 % reduction of nitrogen fertilization, the nitrate concentration will decrease on average by 18 mg L-1.

SERVIR: Connecting Space to Village

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Flores Cordova, Africa Ixmucan

2018-01-01

From space, we can view our planet in new ways. SERVIR empowers people in developing countries to use that view for gaining knowledge and insights about their environments and adaptation to a changing climate. We work with regional decision-makers to foster use of Earth observation satellite data, GIS, and predictive models for addressing water and land use, natural disasters, agricultural problems, biodiversity, and more. These tools can improve the lives, livelihoods, safety, and future of people in communities around the world.

Wildlife habitat connectivity in the changing climate of New York's Hudson Valley.

PubMed

Howard, Timothy G; Schlesinger, Matthew D

2013-09-01

Maintaining and restoring connectivity are key adaptation strategies for biodiversity conservation under climate change. We present a novel combination of species distribution and connectivity modeling using current and future climate regimes to prioritize connections among populations of 26 rare species in New York's Hudson Valley. We modeled patches for each species for each time period and modeled potential connections among habitat patches by finding the least-cost path for every patch-to-patch connection. Finally, we aggregated these patches and paths to the tax parcel, commonly the primary unit of conservation action. Under future climate regimes, suitable habitat was predicted to contract or appear upslope and farther north. On average, predicted patches were nine times smaller and paths were twice as long under future climate. Parcels within the Hudson Highlands, Shawangunk Ridge, Catskill Mountains, and Harlem Valley had high species overlap, with areas upslope and northward increasing in importance over time. We envision that land managers and conservation planners can use these results to help prioritize parcel-level conservation and management and thus support biodiversity adaptation to climate change. © 2013 New York Academy of Sciences.

Assessing spatiotemporal changes in forest carbon turnover times in observational data and models

NASA Astrophysics Data System (ADS)

Yu, K.; Smith, W. K.; Trugman, A. T.; van Mantgem, P.; Peng, C.; Condit, R.; Anderegg, W.

2017-12-01

Forests influence global carbon and water cycles, biophysical land-atmosphere feedbacks, and atmospheric composition. The capacity of forests to sequester atmospheric CO2 in a changing climate depends not only on the response of carbon uptake (i.e., gross primary productivity) but also on the simultaneous change in carbon residence time. However, changes in carbon residence with climate change are uncertain, impacting the accuracy of predictions of future terrestrial carbon cycle dynamics. Here, we use long-term forest inventory data representative of tropical, temperate, and boreal forests; satellite-based estimates of net primary productivity and vegetation carbon stock; and six models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to investigate spatiotemporal trends in carbon residence time and its relation to climate. Forest inventory and satellite-based estimates of carbon residence time show a pervasive decreasing trend across global forests. In contrast, the CMIP5 models diverge in predicting historical and future trends in carbon residence time. Divergence across CMIP5 models indicate carbon turnover times are not well constrained by observations, which likely contributes to large variability in future carbon cycle projections.

Welcome to NASA's Earth Science Enterprise: Educational CD-ROM Activity Supplement

NASA Technical Reports Server (NTRS)

1999-01-01

Since its inception in 1958, NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow, and their influence on weather and climate. We now understand that the key to gaining a better understanding of the global environment is exploring how the Earth's systems of air, land, water, and life interact with each other. This approach-called Earth Systems Science-blends together fields like meteorology, oceanography, geology, and biology. In 1991, NASA launched a more comprehensive program to study the Earth as an integrated environmental system. They call it NASA's Earth Science Enterprise. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). EOS is series of satellites to be launched over the next two decades that will be used to intensively study the Earth, with the hopes of expanding our under- standing of how natural processes affect us, and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, the ability to predict how the climate will change in the future. Today's program is laying the foundation for long-term environmental and climate monitoring and prediction. Potentially, this will provide the understanding needed in the future to support difficult decisions regarding the Earth's environment.

Aquifer-System Compaction and Land Subsidence: Measurements, Analyses, and Simulations-the Holly Site, Edwards Air Force Base, Antelope Valley, California

USGS Publications Warehouse

Sneed, Michelle; Galloway, Devin L.

2000-01-01

Land subsidence resulting from ground-water-level declines has long been recognized as a problem in Antelope Valley, California. At Edwards Air Force Base (EAFB), ground-water extractions have caused more than 150 feet of water-level decline, resulting in nearly 4 feet of subsidence. Differential land subsidence has caused sinklike depressions and earth fissures and has accelerated erosion of the playa lakebed surface of Rogers Lake at EAFB, adversely affecting the runways on the lakebed which are used for landing aircraft such as the space shuttles. Since 1990, about 0.4 foot of aquifer-system compaction has been measured at a deep (840 feet) borehole extensometer (Holly site) at EAFB. More than 7 years of paired ground-water-level and aquifer-system compaction measurements made at the Holly site were analyzed for this study. Annually, seasonal water-level fluctuations correspond to steplike variations in aquifer-system compaction; summer water-level drawdowns are associated with larger rates of compaction, and winter water-level recoveries are associated with smaller rates of compaction. The absence of aquifer-system expansion during recovery is consistent with the delayed drainage and resultant delayed, or residual, compaction of thick aquitards. A numerical one-dimensional MODFLOW model of aquitard drainage was used to refine estimates of aquifer-system hydraulic parameters that control compaction and to predict potential future compaction at the Holly site. The analyses and simulations of aquifer-system compaction are based on established theories of aquitard drainage. Historical ground-water-level and land-subsidence data collected near the Holly site were used to constrain simulations of aquifer-system compaction and land subsidence at the site for the period 1908?90, and ground-water-level and aquifer- system compaction measurements collected at the Holly site were used to constrain the model for the period 1990?97. Model results indicate that two thick aqui- tards, which total 129 feet or about half the aggregate thickness of all the aquitards penetrated by the Holly boreholes, account for most (greater than 99 percent) of the compaction measured at the Holly site during the period 1990?97. The results of three scenarios of future water-level changes indicate that these two thick aquitards account for most of the future compaction. The results also indicate that if water levels decline to about 30 feet below the 1997 water levels an additional 1.7 feet of compaction may occur during the next 30 years. If water levels remain at 1997 levels, the model predicts that only 0.8 foot of compaction may occur during the same period, and even if water levels recover to about 30 feet above 1997 water levels, another 0.5 foot of compaction may occur in the next 30 years. In addition, only a portion of the compaction that ultimately will occur likely will occur within the next 30 years; therefore, the residual compaction and associated land subsidence attributed to slowly equilibrating aquitards is important to consider in the long-term management of land and water resources at EAFB.

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snyder, M.A.; Kueppers, L.M.; Sloan, L.C.

In the western United States, more than 30,500 square miles has been converted to irrigated agriculture and urban areas. This study compares the climate responses of four regional climate models (RCMs) to these past land-use changes. The RCMs used two contrasting land cover distributions: potential natural vegetation, and modern land cover that includes agriculture and urban areas. Three of the RCMs represented irrigation by supplementing soil moisture, producing large decreases in August mean (-2.5 F to -5.6 F) and maximum (-5.2 F to -10.1 F) 2-meter temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture alsomore » resulted in large increases in relative humidity (9 percent 36 percent absolute change). Only one of the RCMs produced increases in summer minimum temperature. Converting natural vegetation to urban land cover produced modest but discernable climate effects in all models, with the magnitude of the effects dependent upon the preexisting vegetation type. Overall, the RCM results indicate that land use change impacts are most pronounced during the summer months, when surface heating is strongest and differences in surface moisture between irrigated land and natural vegetation are largest. The irrigation effect on summer maximum temperatures is comparable in magnitude (but opposite in sign) to predicted future temperature change due to increasing greenhouse gas concentrations.« less

Risk perception, future land use and stewardship: comparison of attitudes about Hanford Site and Idaho National Engineering and Environmental Laboratory.

PubMed

Burger, J; Sanchez, J; Roush, D; Gochfeld, M

2001-04-01

With the ending of the Cold War, the Department of Energy (DOE) is evaluating mission, future land use and stewardship of departmental facilities. This paper compares the environmental concerns and future use preferences of 351 people interviewed at Lewiston, Idaho, about the Hanford Site and Idaho National Engineering and Environmental Laboratory (INEEL), two of DOE's largest sites. Although most subjects lived closer to Hanford than INEEL, most resided in the same state as INEEL. Therefore their economic interests might be more closely allied with INEEL, while their health concerns might be more related to Hanford. Few lived close enough to either site to be directly affected economically. We test the null hypotheses that there are no differences in environmental concerns and future land-use preferences as a function of DOE site, sex, age and education. When asked to list their major concerns about the sites, more people listed human health and safety, and environmental concerns about Hanford compared to INEEL. When asked to list their preferred future land uses, 49% of subjects did not have any for INEEL, whereas only 35% did not know for Hanford. The highest preferred land uses for both sites were as a National Environmental Research Park (NERP), and for camping, hunting, hiking, and fishing. Except for returning the land to the tribes and increased nuclear storage, subjects rated all future uses as more preferred at INEEL than Hanford. Taken together, these data suggest that the people interviewed know more about Hanford, are more concerned about Hanford, rate recreational uses and NERP as their highest preferred land use, and feel that INEEL is more suited for most land uses than Handford. Overall rankings for future land uses were remarkably similar between the sites, indicating that for these stakeholders, DOE lands should be preserved for research and recreation. These preferences should be taken into account when planning for long-term stewardship at these two DOE sites.

Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change

USGS Publications Warehouse

Wilson, Tamara; Sleeter, Benjamin M.; Cameron, D. Richard

2017-01-01

With growing demand and highly variable inter-annual water supplies, California’s water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as “lowest of the low” and “highest of the high” anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm3) in the lowest of the low scenario and decreased 0.8 Bm3 in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm3), high agricultural expansion (+4.6 Bm3), and high urbanization (+2.1 Bm3) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories.

Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change

PubMed Central

Sleeter, Benjamin M.; Cameron, D. Richard

2017-01-01

With growing demand and highly variable inter-annual water supplies, California’s water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as “lowest of the low” and “highest of the high” anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm3) in the lowest of the low scenario and decreased 0.8 Bm3 in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm3), high agricultural expansion (+4.6 Bm3), and high urbanization (+2.1 Bm3) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories. PMID:29088254

Forecasting the effects of land use scenarios on farmland birds reveal a potential mitigation of climate change impacts.

PubMed

Princé, Karine; Lorrillière, Romain; Barbet-Massin, Morgane; Léger, François; Jiguet, Frédéric

2015-01-01

Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.

Drought, Fire and Insects in Western US Forests: Observations to Improve Regional Land System Modeling

NASA Astrophysics Data System (ADS)

Law, B. E.; Yang, Z.; Berner, L. T.; Hicke, J. A.; Buotte, P.; Hudiburg, T. W.

2015-12-01

Drought, fire and insects are major disturbances in the western US, and conditions are expected to get warmer and drier in the future. We combine multi-scale observations and modeling with CLM4.5 to examine the effects of these disturbances on forests in the western US. We modified the Community Land Model, CLM4.5, to improve simulated drought-related mortality in forests, and prediction of insect outbreaks under future climate conditions. We examined differences in plant traits that represent species variation in sensitivity to drought, and redefined plant groupings in PFTs. Plant traits, including sapwood area: leaf area ratio and stemwood density were strongly correlated with water availability during the ecohydrologic year. Our database of co-located observations of traits for 30 tree species was used to produce parameterization of the model by species groupings according to similar traits. Burn area predicted by the new fire model in CLM4.5 compares well with recent years of GFED data, but has a positive bias compared with Landsat-based MTBS. Biomass mortality over recent decades increased, and was captured well by the model in general, but missed mortality trends of some species. Comparisons with AmeriFlux data showed that the model with dynamic tree mortality only (no species trait improvements) overestimated GPP in dry years compared with flux data at semi-arid sites, and underestimated GPP at more mesic sites that experience dry summers. Simulations with both dynamic tree mortality and species trait parameters improved estimates of GPP by 17-22%; differences between predicted and observed NEE were larger. Future projections show higher productivity from increased atmospheric CO2 and warming that somewhat offsets drought and fire effects over the next few decades. Challenges include representation of hydraulic failure in models, and availability of species trait and carbon/water process data in disturbance- and drought-impacted regions.

Relative impacts of land use and climate change on summer precipitation in the Netherlands

NASA Astrophysics Data System (ADS)

Daniels, Emma; Lenderink, Geert; Hutjes, Ronald; Holtslag, Albert

2016-10-01

The effects of historic and future land use on precipitation in the Netherlands are investigated on 18 summer days with similar meteorological conditions. The days are selected with a circulation type classification and a clustering procedure to obtain a homogenous set of days that is expected to favor land impacts. Changes in precipitation are investigated in relation to the present-day climate and land use, and from the perspective of future climate and land use. To that end, the weather research and forecasting (WRF) model is used with land use maps for 1900, 2000, and 2040. In addition, a temperature perturbation of +1 °C assuming constant relative humidity is imposed as a surrogate climate change scenario. Decreases in precipitation of, respectively, 3-5 and 2-5 % are simulated following conversion of historic to present, and present to future, land use. The temperature perturbation under present land use conditions increases precipitation amounts by on average 7-8 % and amplifies precipitation intensity. However, when also considering future land use, the increase is reduced to 2-6 % on average, and no intensification of extreme precipitation is simulated. In all, the simulated effects of land use changes on precipitation in summer are smaller than the effects of climate change, but are not negligible.

Harmonisation of Global Land-Use Scenarios for the Period 1500-2100 for IPCC-AR5

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hurtt, George; Chini, Louise Parsons; Frolking, Steve

2009-06-01

In preparation for the fifth Intergovernmental Panel on Climate Change climate change assessment (IPCC-AR5), the international community is developing new advanced computer models (CMs) to address the combined effects of human activities (e.g. land-use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being developed by four Integrated Assessment Modeling teams (IAMs) to be used as input to the CMs for future climate projections. The diversity of requirements and approaches among CMs and IAMs for tracking land-use changes (past, present, and future), presents major challenges for treating land-usemore » comprehensively and consistently between these communities. As part of an international working group, we have been working to meet these challenges by developing a "harmonized" set of land-use change scenarios that smoothly connects gridded historical reconstructions of land-use with future projections, in a format required by CMs. This approach to harmonizing the treatment of land-use between two key modeling communities, CMs and IAMs, represents a major advance that will facilitate more consistent and fuller treatments of land-use/land-use change effects including both CO2 emissions and corresponding land-surface changes.« less

Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

NASA Astrophysics Data System (ADS)

Tsarouchi, Gina; Buytaert, Wouter

2018-02-01

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

NASA Technical Reports Server (NTRS)

Diallo, Ousmane H.

2012-01-01

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Assessing Hydrologic Impacts of Future Land Cover Change Scenarios in the South Platte River Basin (CO, WY, & NE) and the San Pedro River Basin (U.S./Mexico).

NASA Astrophysics Data System (ADS)

Barlow, J. E.; Burns, I. S.; Guertin, D. P.; Kepner, W. G.; Goodrich, D. C.

2016-12-01

Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology to characterize hydrologic impacts from future urban growth through time that was developed and applied on the San Pedro River Basin was expanded and utilized on the South Platte River Basin as well. Future urban growth is represented by housing density maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land-Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and implement a methodology for adapting the ICLUS data for use in AGWA as an approach to evaluate impacts of development on water-quantity and -quality, 2) present, evaluate, and compare results from scenarios for watersheds in two different geographic and climatic regions, 3) determine watershed specific implications of this type of future land cover change analysis.

Future export of particulate and dissolved organic carbon from land to coastal zones of the Baltic Sea

NASA Astrophysics Data System (ADS)

Strååt, Kim Dahlgren; Mörth, Carl-Magnus; Undeman, Emma

2018-01-01

The Baltic Sea is a semi-enclosed brackish sea in Northern Europe with a drainage basin four times larger than the sea itself. Riverine organic carbon (Particulate Organic Carbon, POC and Dissolved Organic Carbon, DOC) dominates carbon input to the Baltic Sea and influences both land-to-sea transport of nutrients and contaminants, and hence the functioning of the coastal ecosystem. The potential impact of future climate change on loads of POC and DOC in the Baltic Sea drainage basin (BSDB) was assessed using a hydrological-biogeochemical model (CSIM). The changes in annual and seasonal concentrations and loads of both POC and DOC by the end of this century were predicted using three climate change scenarios and compared to the current state. In all scenarios, overall increasing DOC loads, but unchanged POC loads, were projected in the north. In the southern part of the BSDB, predicted DOC loads were not significantly changing over time, although POC loads decreased in all scenarios. The magnitude and significance of the trends varied with scenario but the sign (+ or -) of the projected trends for the entire simulation period never conflicted. Results were discussed in detail for the "middle" CO2 emission scenario (business as usual, a1b). On an annual and entire drainage basin scale, the total POC load was projected to decrease by ca 7% under this scenario, mainly due to reduced riverine primary production in the southern parts of the BSDB. The average total DOC load was not predicted to change significantly between years 2010 and 2100 due to counteracting decreasing and increasing trends of DOC loads to the six major sub-basins in the Baltic Sea. However, predicted seasonal total loads of POC and DOC increased significantly by ca 46% and 30% in winter and decreased by 8% and 21% in summer over time, respectively. For POC the change in winter loads was a consequence of increasing soil erosion and a shift in duration of snowfall and onset of the spring flood impacting the input of terrestrial litter, while reduced primary production mainly explained the differences predicted in summer. The simulations also showed that future changes in POC and DOC export can vary significantly across the different sub-basins of the Baltic Sea. These changes in organic carbon input may impact future coastal food web structures e.g. by influencing bacterial and phytoplankton production in coastal zones, which in turn may have consequences at higher trophic levels.

How to Quantify Human-environment Interactions in the Past: A Global Historical Land Use Data Set for the Holocene

NASA Astrophysics Data System (ADS)

Klein Goldewijk, K.

2015-12-01

Land use plays an important role in the climate system. Many ecosystem processes are directly or indirectly climate driven, and together with human driven land use changes, they determine how the land surface will evolve through time. To assess the effects of land cover changes on the climate system, models are required which are capable of simulating interactions between the involved components of the Earth system. Since driving forces for global environmental change differ among regions, a geographically (spatially) explicit modeling approach is called for, so that it can be incorporated in global and regional (climate and/or biophysical) change models in order to enhance our understanding of the underlying processes and thus improving future projections.Some researchers suggest that mankind has shifted from living in the Holocene (~emergence of agriculture) into the Anthropocene (~humans capable of changing the Earth' atmosphere) since the start of the Industrial Revolution. But in the light of the sheer size and magnitude of some historical land use changes (e.g. the Black Plague in the 14th century and the aftermath of the Colombian Exchange in the 16th century), some believe that this point might have occurred earlier in time. There are still many uncertainties and gaps in our knowledge about the importance of land use (change) in the global biogeochemical cycle, and it is crucial that researchers from other disciplines are involved in decreasing the uncertainties.Thus, integrated records of the co-evolving human-environment system over millennia are needed to provide a basis for a deeper understanding of the present and for forecasting the future. This requires the major task of assembling and integrating regional and global historical, archaeological, and paleo-environmental records. Humans cannot predict the future. Here I present a tool for such long term global change studies; it is the latest update (v 3.2) of the History Database of the Global Environment (HYDE), which tries to incorporate many of these cross-disciplinary records and create thus new and more accurate estimates of the underlying demographic and agricultural driving factors for the whole Holocene. Estimates include population, cropland, pasture, rangeland, irrigation, rice, and built-up area.

78 FR 40499 - Public Land Order No. 7818; Withdrawal of Public Lands for the Protection and Preservation of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... Land Order No. 7818; Withdrawal of Public Lands for the Protection and Preservation of Solar Energy Zones for Future Energy Development; Arizona, California, Colorado, Nevada, New Mexico, and Utah AGENCY... existing rights, for a period of 20 years to protect 17 Solar Energy Zones (SEZ) for future solar energy...

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE PAGES

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; ...

2017-07-06

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

DOE PAGES

De Kauwe, M. G.; Zhou, S. -X.; Medlyn, B. E.; ...

2015-12-21

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSMmore » and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Furthermore, our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.« less

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by themore » observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.« less

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat is also predicted throughout the region. Results have direct application to management issues of habitat connectivity, forest land protection and acquisition, and active management solutions such as transplanting or assisted migration. Although this analysis considers only one driver of forest habitat distribution, consideration of hydrologic derivatives at a fine scale explains current forest community distributions and provides a far more informed perspective on potential future forest distributions. Results demonstrate the utility of fine-scale modeling and provide landscape managers and conservation agencies valuable management tools in fine-scale future forest scenarios and a framework for evaluating forest resiliency in a changing climate.

Land use in the lake states region: an analysis of past trends and projections of future changes.

Treesearch

Thomas E. Mauldin; Andrew J. Plantinga; Ralph J. Alig

1999-01-01

This paper presents the historic trends and future projections of forest, farm, and urban land uses for the Lake States of Michigan, Minnesota, and Wisconsin. Since the 1950s, forest and farm land have been decreasing, and urban and other land uses have been increasing throughout the Lake States. Forest, crop, and pasture land have decreased in the region by 3.2, 5.4...

Predicting groundwater recharge for varying land cover and climate conditions - a global meta-study

NASA Astrophysics Data System (ADS)

Mohan, Chinchu; Western, Andrew W.; Wei, Yongping; Saft, Margarita

2018-05-01

Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors, and to predict groundwater recharge at 0.5° resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981-2014) was 134 mm yr-1 with a prediction error ranging from -8 to 10 mm yr-1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.

Through the eyes of children: perceptions of environmental change in tropical forests.

PubMed

Pellier, Anne-Sophie; Wells, Jessie A; Abram, Nicola K; Gaveau, David; Meijaard, Erik

2014-01-01

This study seeks to understand children's perceptions of their present and future environments in the highly biodiverse and rapidly changing landscapes of Kalimantan, Indonesian Borneo. We analyzed drawings by children (target age 10-15 years) from 22 villages, which show how children perceive the present conditions of forests and wildlife surrounding their villages and how they expect conditions to change over the next 15 years. Analyses of picture elements and their relationships to current landscape variables indicate that children have a sophisticated understanding of their environment and how different environmental factors interact, either positively or negatively. Children appear to have landscape-dependent environmental perceptions, showing awareness of past environmental conditions and many aspects of recent trends, and translating these into predictions for future environmental conditions. The further removed their present landscape is from the originally forested one, the more environmental change they expect in the future, particularly declines in forest cover, rivers, animal diversity and increases in temperature and natural disasters. This suggests that loss of past perceptions and associated "shifting environmental baselines" do not feature strongly among children on Borneo, at least not for the perceptions we investigated here. Our findings that children have negative expectations of their future environmental conditions have important political implications. More than other generations, children have a stake in ensuring that future environmental conditions support their long-term well-being. Understanding what drives environmental views among children, and how they consider trade-offs between economic development and social and environmental change, should inform optimal policies on land use. Our study illuminates part of the complex interplay between perceptions of land cover and land use change. Capturing the views of children through artistic expressions provides a potentially powerful tool to influence public and political opinions, as well as a valuable approach for developing localized education and nature conservation programs.

Through the Eyes of Children: Perceptions of Environmental Change in Tropical Forests

PubMed Central

Pellier, Anne-Sophie; Wells, Jessie A.; Abram, Nicola K.; Gaveau, David; Meijaard, Erik

2014-01-01

This study seeks to understand children's perceptions of their present and future environments in the highly biodiverse and rapidly changing landscapes of Kalimantan, Indonesian Borneo. We analyzed drawings by children (target age 10–15 years) from 22 villages, which show how children perceive the present conditions of forests and wildlife surrounding their villages and how they expect conditions to change over the next 15 years. Analyses of picture elements and their relationships to current landscape variables indicate that children have a sophisticated understanding of their environment and how different environmental factors interact, either positively or negatively. Children appear to have landscape-dependent environmental perceptions, showing awareness of past environmental conditions and many aspects of recent trends, and translating these into predictions for future environmental conditions. The further removed their present landscape is from the originally forested one, the more environmental change they expect in the future, particularly declines in forest cover, rivers, animal diversity and increases in temperature and natural disasters. This suggests that loss of past perceptions and associated “shifting environmental baselines” do not feature strongly among children on Borneo, at least not for the perceptions we investigated here. Our findings that children have negative expectations of their future environmental conditions have important political implications. More than other generations, children have a stake in ensuring that future environmental conditions support their long-term well-being. Understanding what drives environmental views among children, and how they consider trade-offs between economic development and social and environmental change, should inform optimal policies on land use. Our study illuminates part of the complex interplay between perceptions of land cover and land use change. Capturing the views of children through artistic expressions provides a potentially powerful tool to influence public and political opinions, as well as a valuable approach for developing localized education and nature conservation programs. PMID:25093658

A novel assessment of the role of land-use and land-cover change in the global carbon cycle, using a new Dynamic Global Vegetation Model version of the CABLE land surface model

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Smith, Benjamin; Nieradzik, Lars; Briggs, Peter; Canadell, Josep

2017-04-01

In recent decades, terrestrial ecosystems have sequestered around 1.2 PgC y-1, an amount equivalent to 20% of fossil-fuel emissions. This land carbon flux is the net result of the impact of changing climate and CO2 on ecosystem productivity (CO2-climate driven land sink ) and deforestation, harvest and secondary forest regrowth (the land-use change (LUC) flux). The future trajectory of the land carbon flux is highly dependent upon the contributions of these processes to the net flux. However their contributions are highly uncertain, in part because the CO2-climate driven land sink and LUC components are often estimated independently, when in fact they are coupled. We provide a novel assessment of global land carbon fluxes (1800-2015) that integrates land-use effects with the effects of changing climate and CO2 on ecosystem productivity. For this, we use a new land-use enabled Dynamic Global Vegetation Model (DGVM) version of the CABLE land surface model, suitable for use in attributing changes in terrestrial carbon balance, and in predicting changes in vegetation cover and associated effects on land-atmosphere exchange. In this model, land-use-change is driven by prescribed gross land-use transitions and harvest areas, which are converted to changes in land-use area and transfer of carbon between pools (soil, litter, biomass, harvested wood products and cleared wood pools). A novel aspect is the treatment of secondary woody vegetation via the coupling between the land-use module and the POP (Populations Order Physiology) module for woody demography and disturbance-mediated landscape heterogeneity. Land-use transitions to and from secondary forest tiles modify the patch age distribution within secondary-vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. The resulting secondary forest patch age distribution also influences the magnitude of the secondary forest harvest and clearance fluxes, with oldest patches (high biomass) being preferentially harvested, and youngest patches (low biomass) being preferentially cleared. Our results, which agree well with the net land flux derived from the global carbon budget, are used for a process-attribution of the land carbon sink. Use of multiple constraints provides confidence in our process-attribution: we use observation-based data sets to evaluate predictions of global spatial distributions of vegetation cover, evaporation, gross primary production, biomass and soil carbon; interannual variability of the global terrestrial carbon sink; forest allometric relations and age-effects on net primary production.

Mars exobiology landing sites for future exploration

NASA Technical Reports Server (NTRS)

Landheim, Ragnhild; Greeley, Ronald; Desmarais, David; Farmer, Jack D.; Klein, Harold

1993-01-01

The selection of landing sites for Exobiology is an important issue for planning for future Mars missions. Results of a recent site selection study which focused on potential landing sites described in the Mars Landing Site Catalog are presented. In addition, basic Exobiology science objectives in Mars exploration are reviewed, and the procedures used in site evaluation and prioritization are outlined.

43 CFR 431.9 - Future regulations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 1 2011-10-01 2011-10-01 false Future regulations. 431.9 Section 431.9 Public Lands: Interior Regulations Relating to Public Lands BUREAU OF RECLAMATION, DEPARTMENT OF THE INTERIOR GENERAL REGULATIONS FOR POWER GENERATION, OPERATION, MAINTENANCE, AND REPLACEMENT AT THE BOULDER...

43 CFR 431.9 - Future regulations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Future regulations. 431.9 Section 431.9 Public Lands: Interior Regulations Relating to Public Lands BUREAU OF RECLAMATION, DEPARTMENT OF THE INTERIOR GENERAL REGULATIONS FOR POWER GENERATION, OPERATION, MAINTENANCE, AND REPLACEMENT AT THE BOULDER...

Empirical Prediction of Aircraft Landing Gear Noise

NASA Technical Reports Server (NTRS)

Golub, Robert A. (Technical Monitor); Guo, Yue-Ping

2005-01-01

This report documents a semi-empirical/semi-analytical method for landing gear noise prediction. The method is based on scaling laws of the theory of aerodynamic noise generation and correlation of these scaling laws with current available test data. The former gives the method a sound theoretical foundation and the latter quantitatively determines the relations between the parameters of the landing gear assembly and the far field noise, enabling practical predictions of aircraft landing gear noise, both for parametric trends and for absolute noise levels. The prediction model is validated by wind tunnel test data for an isolated Boeing 737 landing gear and by flight data for the Boeing 777 airplane. In both cases, the predictions agree well with data, both in parametric trends and in absolute noise levels.

A stochastic Forest Fire Model for future land cover scenarios assessment

NASA Astrophysics Data System (ADS)

D'Andrea, M.; Fiorucci, P.; Holmes, T. P.

2010-10-01

Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary - each cell either contains a tree or it is empty - and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM), addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity.

PubMed

Swann, Abigail L S; Hoffman, Forrest M; Koven, Charles D; Randerson, James T

2016-09-06

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

PubMed Central

Koven, Charles D.; Randerson, James T.

2016-01-01

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment. PMID:27573831

A methodology to estimate the future extent of dryland salinity in the southwest of Western Australia.

PubMed

Caccetta, Peter; Dunne, Robert; George, Richard; McFarlane, Don

2010-01-01

In the southwestern agricultural region of Western Australia, the clearing of the original perennial vegetation for annual vegetation-based dryland agriculture has lead to rising saline groundwater levels. This has had effects such as reduced productivity of agricultural land, death of native vegetation, reduced stream water quality and infrastructure damage. These effects have been observed at many locations within the 18 million ha of cleared land. This has lead to efforts to quantify, in a spatially explicit way, the historical and likely future extent of the area affected, with the view to informing management decisions. This study was conducted to determine whether the likely future extent of the area affected by dryland salinity could be estimated by means of developing spatially explicit maps for use in management and planning. We derived catchment-related variables from digital elevation models and perennial vegetation presence/absence maps. We then used these variables to predict the salinity hazard extent by applying a combination of decision tree classification and morphological image processing algorithms. Sufficient objective data such as groundwater depth, its rate of rise, and its concentration of dissolved salts were generally not available, so we used regional expert opinion (derived from the limited existing studies on salinity hazard extent) as training and validation data. We obtained an 87% agreement in the salinity hazard extent estimated by this method compared with the validation data, and conclude that the maps are sufficient for planning. We estimate that the salinity hazard extent is 29.7% of the agricultural land.

Landscape changes, traditional ecological knowledge and future scenarios in the Alps: A holistic ecological approach.

PubMed

Tattoni, Clara; Ianni, Elena; Geneletti, Davide; Zatelli, Paolo; Ciolli, Marco

2017-02-01

In recent decades, a dramatic landscape change has occurred in the European alpine region: open areas have been naturally recolonized by forests as traditional agricultural and forest activities were reduced and reorganized. Land use changes (LUC) are generally measured through GIS and photo interpretation techniques, but despite many studies focused on this phenomenon and its effects on biodiversity and on the environment in general, there is a lack of information about the transformation of the human-environment connection. The study of Traditional Ecological Knowledge (TEK), such as the ability to recognize wild plants used as medicine or food, can suggest how this connection evolved through time and generations. This work investigates the relationship between the natural forest cover expansion that influences the loss of open areas and the loss of TEK. Different data sources and approaches were used to address the topic in all its complexity: a mix of questionnaire investigations, historical maps, GIS techniques and modelling were used to analyse past land use changes and predict future scenarios. The study area, Trentino, Italy, is paradigmatic of the alpine situation, and the land use change in the region is well documented by different studies, which were reviewed and compared in this paper. Our findings suggest that open area loss can be used as a good proxy to highlight the present state and to produce future scenarios of Traditional Ecological Knowledge. This could increase awareness of the loss of TEK in other Alpine regions, where data on TEK are lacking, but where environmental trends are comparable. Copyright © 2016 Elsevier B.V. All rights reserved.

Future climate and land uses effects on flow and nutrient loads of a Mediterranean catchment in South Australia.

PubMed

Shrestha, Manoj K; Recknagel, Friedrich; Frizenschaf, Jacqueline; Meyer, Wayne

2017-07-15

Mediterranean catchments experience already high seasonal variability alternating between dry and wet periods, and are more vulnerable to future climate and land use changes. Quantification of catchment response under future changes is particularly crucial for better water resources management. This study assessed the combined effects of future climate and land use changes on water yield, total nitrogen (TN) and total phosphorus (TP) loads of the Mediterranean Onkaparinga catchment in South Australia by means of the eco-hydrological model SWAT. Six different global climate models (GCMs) under two representative concentration pathways (RCPs) and a hypothetical land use change were used for future simulations. The climate models suggested a high degree of uncertainty, varying seasonally, in both flow and nutrient loads; however, a decreasing trend was observed. Average monthly TN and TP load decreased up to -55% and -56% respectively and were found to be dependent on flow magnitude. The annual and seasonal water yield and nutrient loads may only slightly be affected by envisaged land uses, but significantly altered by intermediate and high emission scenarios, predominantly during the spring season. The combined scenarios indicated the possibility of declining flow in future but nutrient enrichment in summer months, originating mainly from the land use scenario, that may elevate the risk of algal blooms in downstream drinking water reservoir. Hence, careful planning of future water resources in a Mediterranean catchment requires the assessment of combined effects of multiple climate models and land use scenarios on both water quantity and quality. Copyright © 2017 Elsevier B.V. All rights reserved.

The Effects of Changing Land Use and Climate on the Hydrology and Carbon Budget of Lake Simcoe Watershed, Ontario, Canada

NASA Astrophysics Data System (ADS)

Oni, Stephen Kayode

The Lake Simcoe watershed (LSW) has experienced significant population growth and is under pressure from development. This has led to land use changes in the watershed in addition to the global climate change that is impacting every region of the world. In this thesis, remote sensing analysis, statistics and process-based modelling approaches were used to better understand dissolved organic carbon (DOC) and runoff dynamics in the changing landscape of LSW. The process-based approach involved the use of the HBV (Hydrologiska Byrans Vattenbalansavdelning) rainfall runoff model and the Integrated Catchment Model for Carbon (INCA-C). Statistical downscaling of the Canadian General Circulation Model (CGCM3) was used to predict the impact of climate change under the IPCC (Intergovernmental Panel on Climate Change) A1B and A2 scenarios. There was a significant land use change in LSW between 1994 and 2009 with a positive monotonic trend in runoff ratio across tributaries. Large increase in runoff ratio without corresponding increase in precipitation suggested that runoff drains more quickly over the land surfaces; an indication of increasing urban-induced impervious surfaces. However, there was a significant increase in air temperature (MK = 0.315; p<0.01) and precipitation (MK = 0.290; p<0.01) outside the fifteen year (1994-2009) window. This translated to an increase in air temperature of ˜0.7°C and precipitation by ˜6.3% at the end of the forty year period (1960-2000). This suggested that historical meteorological conditions in the LSW have evolved to a warmer-wetter condition in the recent time and this might serve as a pointer of future conditions if the current trend persists. Both A1B and A2 scenarios predicted an increase in air temperature by a maximum of 1.4°C by 2050 and up to 3.5°C by 2100 relative to the baseline period (1960-2000). HBV predicted a largest variability in the spring and winter season's runoff regimes (2020-2050) under both A1B and A2 scenarios. A 5% increase in DOC concentration and a 6% increase in flux were observed between period 1 (1994-1997) and period 2 (2007-2009). The observed increases were driven by spring (20%) and summer (26%). INCA-C predicted a positive monotonic increase in long-term DOC concentrations (2020-2100) in surface waters draining into Lake Simcoe under both scenarios with the largest seasonal variations in DOC concentrations predicted to occur in the summer months. This indicates the sensitivity of surface water quantity-quality to rising air temperature with the possibility of an increase in CO2 emissions from the rivers in the future. Understanding the processes that mediate DOC mobilization into Lake Simcoe from its catchment may lead to improvements in watershed management and a better understanding of other carbon dependent biogeochemical processes such as mercury. Keywords: CGCM, Climate change, Dissolved organic carbon, Environmental modelling, HBV model, Hydrology, INCA-C, Lake Simcoe, Land use change, Remote sensing, SDSM, Statistical downscaling.

Analysis of Unit Breakpoints in Land Combat

DTIC Science & Technology

1975-03-01

movement. The The pý:ocedure used by the commander to designate objccties and decide on courses of action which will attain those objectives is...relevant state variable since it is used to describe the state of an existing system . The state of the system might be thought of as "the minimum amount of...present information about the history of the system which allows one to predict the effect of the past upon the future" (Ref. 341. The first problem

Evaluating land-use change scenarios for the Puget Sound Basin, Washington, within the ecosystem recovery target model-based framework

USGS Publications Warehouse

Villarreal, Miguel; Labiosa, Bill; Aiello, Danielle

2017-05-23

The Puget Sound Basin, Washington, has experienced rapid urban growth in recent decades, with varying impacts to local ecosystems and natural resources. To plan for future growth, land managers often use scenarios to assess how the pattern and volume of growth may affect natural resources. Using three different land-management scenarios for the years 2000–2060, we assessed various spatial patterns of urban growth relative to maps depicting a model-based characterization of the ecological integrity and recent development pressure of individual land parcels. The three scenarios depict future trajectories of land-use change under alternative management strategies—status quo, managed growth, and unconstrained growth. The resulting analysis offers a preliminary assessment of how future growth patterns in the Puget Sound Basin may impact land targeted for conservation and how short-term metrics of land-development pressure compare to longer term growth projections.

Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity

NASA Astrophysics Data System (ADS)

Morris, C. K.; Knighton, J.

2017-12-01

Nitrous oxide is produced from the biological processes of nitrification and denitrification in terrestrial environments and contributes to the greenhouse effect that warms Earth's climate. Large scale modeling can be used to determine how global rate of nitrous oxide production and consumption will shift under future climates. However, accurate modeling of nitrification and denitrification is made difficult by highly parameterized, nonlinear equations. Here we show that the representation of spatial heterogeneity in inputs, specifically soil moisture, causes inaccuracies in estimating the average nitrous oxide production in soils. We demonstrate that when soil moisture is averaged from a spatially heterogeneous surface, net nitrous oxide production is under predicted. We apply this general result in a test of a widely-used global land surface model, the Community Land Model v4.5. The challenges presented by nonlinear controls on nitrous oxide are highlighted here to provide a wider context to the problem of extraordinary denitrification losses in CLM. We hope that these findings will inform future researchers on the possibilities for model improvement of the global nitrogen cycle.

A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall

2004-01-01

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore proper assessment of the urban environment s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning-design and land-atmosphere-ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990-present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as METROMEX studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g. aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes.

Urban change analysis and future growth of Istanbul.

PubMed

Akın, Anıl; Sunar, Filiz; Berberoğlu, Süha

2015-08-01

This study is aimed at analyzing urban change within Istanbul and assessing the city's future growth potential using appropriate approach modeling for the year 2040. Urban growth is a major driving force of land-use change, and spatial and temporal components of urbanization can be identified through accurate spatial modeling. In this context, widely used urban modeling approaches, such as the Markov chain and logistic regression based on cellular automata (CA), were used to simulate urban growth within Istanbul. The distance from each pixel to the urban and road classes, elevation, and slope, together with municipality and land use maps (as an excluded layer), were identified as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986, and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps, and a kappa index of agreement was derived. The results indicate that urban expansion will influence mainly forest areas during the time period of 2013-2040. The urban expansion was predicted as 429 and 327 km(2) with the Markov chain and logistic regression models, respectively.

Future of endemic flora of biodiversity hotspots in India.

PubMed

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.

Future of Endemic Flora of Biodiversity Hotspots in India

PubMed Central

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models. PMID:25501852

Future Scenarios of Livestock and Land Use in Brazil

NASA Astrophysics Data System (ADS)

Costa, M. H.; Abrahão, G. M.

2016-12-01

Brazil currently has about 213 M cattle heads in 151 M ha of pastures. In the last 40 years, both the top 5% and the average stocking rate are increasing exponentially in Brazil, while the relative yield gap has been constant. Using these historical relationships, we estimate future scenarios of livestock and land use in Brazil. We assume a reference scenario for the top 5%, in which pasturelands are adequately fertilized, soil is not compacted and well drained, grasses are never burned, pastures are divided in 8 subdivisions of regular area, are cattle is rotated through the subdivisions. The reference scenario does not consider irrigation or feed supplementation. We calibrate a computer model and run it for the pasturelands throughout the entire country. We conclude that current pastures have about 20% efficiency to raise cattle compared to the reference scenario. Considering the reference scenario, we predict an equilibrium will be reached in about 100 years, with top 5% with about 9.3 heads per ha and the average 4.3 heads per ha, or 600 M heads of livestock. Considering a more pessimistic scenario, which considers an inflection of the curve in present times, we predict an equilibrium will be reached in about 60 years, with the top 5% stocking rate equal to 4.3 heads per ha and the average equal to 2.2 heads per ha, or 300 M heads of livestock. Both cases represent a considerable expansion of the livestock, maybe even higher than the growth of the global demands for beef. These scenarios indicate that not all existing pasturelands need to be used in the future - a significant part of them may be converted to croplands, which will also contribute to the reduction of deforestation.

Impacts of climate and land use changes on regional nutrient export in the South Saskatchewan River catchment

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Wheater, H. S.; Lindenschmidt, K. E.

2016-12-01

Climate and land use changes modify the physical functioning of river catchments and, in particular, influence the transport of nutrients from land to water. In large-scale catchments, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms the largest river system in western Canada. In the past years changes in the land use and new industrial developments in the SSR area have heightened serious concerns about the future of water quality in the catchment and downstream waters. Agricultural activities have increased the supply of manure and fertilizer for cropping. Oil and gas exploitation has also increased the risk of surface water and groundwater contamination. The rapid population growth not only leads to increments in water consumption and wastewater, but in the construction of roads, railways and the expansion of new urban developments that impose hydraulic controls on the catchment hydrology and therefore the sediment and nutrient transport. Consequences of the actual anthropogenic changes have been notorious in reservoirs where algal blooms and signs of eutrophication have become common during certain times of the year. Although environmental agencies are constantly improving the mechanisms to reduce nutrient export into the river and ensure safe water quality standards, further research is needed in order to identify major nutrient sources and quantify nutrient export and also, to assess how nutrients are going to vary as a result of future climate and land use change scenarios. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality regionally, in order to describe spatial and temporal patterns to identify those factors and processes that affect water quality. Climate and land uses change scenarios are incorporated into the model to explain how nutrient export will vary across the catchment in 30, 60 and 90 years from now. Uncertainty of nutrient predictions is also assesses in order to determine the degree of reliability of the estimates.

Impacts of climate and land use changes on regional nutrient export in the South Saskatchewan River catchment

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Wheater, H. S.; Lindenschmidt, K. E.

2015-12-01

Climate and land use changes modify the physical functioning of river catchments and, in particular, influence the transport of nutrients from land to water. In large-scale catchments, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms the largest river system in western Canada. In the past years changes in the land use and new industrial developments in the SSR area have heightened serious concerns about the future of water quality in the catchment and downstream waters. Agricultural activities have increased the supply of manure and fertilizer for cropping. Oil and gas exploitation has also increased the risk of surface water and groundwater contamination. The rapid population growth not only leads to increments in water consumption and wastewater, but in the construction of roads, railways and the expansion of new urban developments that impose hydraulic controls on the catchment hydrology and therefore the sediment and nutrient transport. Consequences of the actual anthropogenic changes have been notorious in reservoirs where algal blooms and signs of eutrophication have become common during certain times of the year. Although environmental agencies are constantly improving the mechanisms to reduce nutrient export into the river and ensure safe water quality standards, further research is needed in order to identify major nutrient sources and quantify nutrient export and also, to assess how nutrients are going to vary as a result of future climate and land use change scenarios. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality regionally, in order to describe spatial and temporal patterns to identify those factors and processes that affect water quality. Climate and land uses change scenarios are incorporated into the model to explain how nutrient export will vary across the catchment in 30, 60 and 90 years from now. Uncertainty of nutrient predictions is also assesses in order to determine the degree of reliability of the estimates.

Does reading scenarios of future land use changes affect willingness to participate in land use planning?

Treesearch

Michelle L. Johnson; Kathleen P. Bell; Mario F. Teisl

2016-01-01

Scenarios of future outcomes often provide context for policy decisions and can be a form of science communication, translating complex and uncertain relationships into stories for a broader audience. We conducted a survey experiment (n = 270) to test the effects of reading land use change scenarios on willingness to participate in land use planning activities. In the...

Forecasts of county-level land uses under three future scenarios: a technical document supporting the Forest Service 2010 RPA Assessment

Treesearch

David N. Wear

2011-01-01

Accurately forecasting future forest conditions and the implications for ecosystem services depends on understanding land use dynamics. In support of the 2010 Renewable Resources Planning Act (RPA) Assessment, we forecast changes in land uses for the coterminous United States in response to three scenarios. Our land use models forecast urbanization in response to the...

Modification of land-atmosphere interactions by CO2 effects: Implications for summer dryness and heat wave amplitude

NASA Astrophysics Data System (ADS)

Lemordant, Léo.; Gentine, Pierre; Stéfanon, Marc; Drobinski, Philippe; Fatichi, Simone

2016-10-01

Plant stomata couple the energy, water, and carbon cycles. We use the framework of Regional Climate Modeling to simulate the 2003 European heat wave and assess how higher levels of surface CO2 may affect such an extreme event through land-atmosphere interactions. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the heat wave impact. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels and of the coupling between the carbon and water cycles is therefore critical to forecasting seasonal climate, water cycle dynamics, and to enhance the accuracy of extreme event prediction under future climate.

Implications of rural-urban migration for conservation of the Atlantic Forest and urban growth in Misiones, Argentina (1970-2030).

PubMed

Izquierdo, Andrea E; Grau, Héctor R; Aide, T Mitchell

2011-05-01

Global trends of increasing rural-urban migration and population urbanization could provide opportunities for nature conservation, particularly in regions where deforestation is driven by subsistence agriculture. We analyzed the role of rural population as a driver of deforestation and its contribution to urban population growth from 1970 to the present in the Atlantic Forest of Argentina, a global conservation priority. We created future land-use-cover scenarios based on human demographic parameters and the relationship between rural population and land-cover change between 1970 and 2006. In 2006, native forest covered 50% of the province, but by 2030 all scenarios predicted a decrease that ranged from 18 to 39% forest cover. Between 1970 and 2001, rural migrants represented 20% of urban population growth and are expected to represent less than 10% by 2030. This modeling approach shows how rural-urban migration and land-use planning can favor nature conservation with little impact on urban areas.

Urban Expansion Modeling Approach Based on Multi-Agent System and Cellular Automata

NASA Astrophysics Data System (ADS)

Zeng, Y. N.; Yu, M. M.; Li, S. N.

2018-04-01

Urban expansion is a land-use change process that transforms non-urban land into urban land. This process results in the loss of natural vegetation and increase in impervious surfaces. Urban expansion also alters the hydrologic cycling, atmospheric circulation, and nutrient cycling processes and generates enormous environmental and social impacts. Urban expansion monitoring and modeling are crucial to understanding urban expansion process, mechanism, and its environmental impacts, and predicting urban expansion in future scenarios. Therefore, it is important to study urban expansion monitoring and modeling approaches. We proposed to simulate urban expansion by combining CA and MAS model. The proposed urban expansion model based on MSA and CA was applied to a case study area of Changsha-Zhuzhou-Xiangtan urban agglomeration, China. The results show that this model can capture urban expansion with good adaptability. The Kappa coefficient of the simulation results is 0.75, which indicated that the combination of MAS and CA offered the better simulation result.

Decadal Recruitment and Mortality of Ponderosa pine Predicted for the 21st Century Under five Downscaled Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.

2008-12-01

Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.

Contribution of knee flexor and extensor strength on sex-specific energy absorption and torsional joint stiffness during drop jumping.

PubMed

Schmitz, Randy J; Shultz, Sandra J

2010-01-01

Lower extremity injury often occurs during abrupt deceleration when attempting to change the body's direction. Although sex-specific biomechanics have been implicated in the greater risk of acute knee injury in women than in men, it is unknown if sex differences in thigh strength affect sex-specific energy absorption and torsional joint stiffness patterns. To determine sex differences in energy absorption patterns and joint stiffnesses of the lower extremity during a drop jump and to determine if these sex differences were predicted by knee extensor and flexor strength. Cross-sectional study. Laboratory environment. Recreationally active, college-aged students (41 women: age  =  22.1 ± 2.9 years, height  =  1.63 ± 0.07 m, mass  =  59.3 ± 8.0 kg; 40 men: age  =  22.4 ± 2.8 years, height  =  1.77 ± 0.1 m, mass  =  80.9 ± 14.1 kg). Participants performed knee flexor and extensor maximal voluntary isometric contractions followed by double-leg drop-jump landings. Lower extremity joint energetics (J × N(-1) × m(-1)) and torsional joint stiffnesses (Nm × N(-1) × m(-1) × degrees(-1)) were calculated for the hip, knee, and ankle during the initial landing phase. Body weight was measured in newtons and height was measured in meters. Sex comparisons were made and sex-specific regressions determined if thigh muscle strength (Nm/kg) predicted sagittal-plane landing energetics and stiffnesses. Women absorbed 69% more knee energy and had 36% less hip torsional stiffness than men. In women, greater knee extensor strength predicted greater knee energy absorption (R(2)  =  0.11, P  =  .04), and greater knee flexor strength predicted greater hip torsional stiffness (R(2)  =  0.12, P  =  .03). Sex-specific biomechanics during the deceleration phase of a drop jump revealed that women used a strategy to attempt to decrease system stiffness. Additionally, only female strength values were predictive of landing energetics and stiffnesses. These findings collectively demonstrated that the task may have been more difficult for women, resulting in a different movement strategy among those with different levels of thigh strength to safely complete the task. Future researchers should look at other predictive factors of observed sex differences.

Synopsis of Precision Landing and Hazard Avoidance (PL&HA) Capabilities for Space Exploration

NASA Technical Reports Server (NTRS)

Robertson, Edward A.

2017-01-01

Until recently, robotic exploration missions to the Moon, Mars, and other solar system bodies relied upon controlled blind landings. Because terrestrial techniques for terrain relative navigation (TRN) had not yet been evolved to support space exploration, landing dispersions were driven by the capabilities of inertial navigation systems combined with surface relative altimetry and velocimetry. Lacking tight control over the actual landing location, mission success depended on the statistical vetting of candidate landing areas within the predicted landing dispersion ellipse based on orbital reconnaissance data, combined with the ability of the spacecraft to execute a controlled landing in terms of touchdown attitude, attitude rates, and velocity. In addition, the sensors, algorithms, and processing technologies required to perform autonomous hazard detection and avoidance in real time during the landing sequence were not yet available. Over the past decade, NASA has invested substantial resources on the development, integration, and testing of autonomous precision landing and hazard avoidance (PL&HA) capabilities. In addition to substantially improving landing accuracy and safety, these autonomous PL&HA functions also offer access to targets of interest located within more rugged and hazardous terrain. Optical TRN systems are baselined on upcoming robotic landing missions to the Moon and Mars, and NASA JPL is investigating the development of a comprehensive PL&HA system for a Europa lander. These robotic missions will demonstrate and mature PL&HA technologies that are considered essential for future human exploration missions. PL&HA technologies also have applications to rendezvous and docking/berthing with other spacecraft, as well as proximity navigation, contact, and retrieval missions to smaller bodies with microgravity environments, such as asteroids.

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

UK Environmental Prediction - integration and evaluation at the convective scale

NASA Astrophysics Data System (ADS)

Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

2016-04-01

Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

Future Climate Impacts on Harmful Algal Blooms in an Agriculturally Dominated Ecosystem

NASA Astrophysics Data System (ADS)

Aloysius, N. R.; Martin, J.; Ludsin, S.; Stumpf, R. P.

2015-12-01

Cyanobacteria blooms have become a major problem worldwide in aquatic ecosystems that receive excessive runoff of limiting nutrients from terrestrial drainage. Such blooms often are considered harmful because they degrade ecosystem services, threaten public health, and burden local economies. Owing to changing agricultural land-use practices, Lake Erie, the most biologically productive of the North American Great Lakes, has begun to undergo a re-eutrophication in which the frequency and extent of harmful algal blooms (HABs) has increased. Continued climate change has been hypothesized to magnify the HAB problem in Lake Erie in the absence of new agricultural management practices, although this hypothesis has yet to be formally tested empirically. Herein, we tested this hypothesis by predicting how the frequency and extent of potentially harmful cyanobacteria blooms will change in Lake Erie during the 21st century under the Intergovernmental Panel on Climate Change Fifth Assessment climate projections in the region. To do so, we used 80 ensembles of climate projections from 20 Global Climate Models (GCMs) and two greenhouse gas emission scenarios (moderate reduction, RCP4.5; business-as-usual, RCP8.5) to drive a spatiotemporally explicit watershed-hydrology model that was linked to several statistical predictive models of annual cyanobacteria blooms in Lake Erie. Owing to anticipated increases in precipitation during spring and warmer temperatures during summer, our ensemble of predictions revealed that, if current land-management practices continue, the frequency of severe HABs in Lake Erie will increase during the 21st century. These findings identify a real need to consider future climate projections when developing nutrient reduction strategies in the short term, with adaptation also needing to be encouraged under both greenhouse gas emissions scenarios in the absence of effective nutrient mitigation strategies.

Future water demand in California under a broad range of land use scenarios

NASA Astrophysics Data System (ADS)

Wilson, T. S.; Sleeter, B. M.; Cameron, D. R.

2016-12-01

California continues to be gripped by the most severe drought on record. Most general circulation models agree the state will continue to warm this century and research suggests persistent, long-term droughts may become the new normal, exacerbating an already uncertain water supply future. Population increases and agricultural intensification will likely stress existing, highly variable inter-annual water supplies even further in coming decades. Using the Land Use and Carbon Scenario Simulator (LUCAS) model, we explore a wide range of potential water demand futures from 2012 to 2062 based on 8 alternative, spatially-explicit (1 km) land use scenarios and land-use related water demand. Scenarios include low and high rates for urbanization, agricultural expansion, and agricultural contraction as well as lowest and highest rates for the combined suite of anthropogenic land uses. Land change values were sampled from county-level historical (1991-2012) land change data and county-level average water use data for urban areas (i.e. municipal and industrial) and annual and perennial cropland. We modeled 100 Monte Carlo simulations for each scenario to better characterize and capture model uncertainty and a range of potential future outcomes. Results show water demand in Mediterranean California was lowest in the low anthropogenic change scenario, dropping an average 2.7 million acre feet (MAF) by 2062. The highest water demand was seen in the high urbanization (+3.2 MAF), high agricultural expansion (+4.1 MAF), and the high anthropogenic (+4.3 MAF) scenarios. Results provide water managers and policy makers with information on diverging land use and water use futures, based on observed land change and water use trends, helping better inform land and resource management decisions.

Exploring uncertainty of Amazon dieback in a perturbed parameter Earth system ensemble.

PubMed

Boulton, Chris A; Booth, Ben B B; Good, Peter

2017-12-01

The future of the Amazon rainforest is unknown due to uncertainties in projected climate change and the response of the forest to this change (forest resiliency). Here, we explore the effect of some uncertainties in climate and land surface processes on the future of the forest, using a perturbed physics ensemble of HadCM3C. This is the first time Amazon forest changes are presented using an ensemble exploring both land vegetation processes and physical climate feedbacks in a fully coupled modelling framework. Under three different emissions scenarios, we measure the change in the forest coverage by the end of the 21st century (the transient response) and make a novel adaptation to a previously used method known as "dry-season resilience" to predict the long-term committed response of the forest, should the state of the climate remain constant past 2100. Our analysis of this ensemble suggests that there will be a high chance of greater forest loss on longer timescales than is realized by 2100, especially for mid-range and low emissions scenarios. In both the transient and predicted committed responses, there is an increasing uncertainty in the outcome of the forest as the strength of the emissions scenarios increases. It is important to note however, that very few of the simulations produce future forest loss of the magnitude previously shown under the standard model configuration. We find that low optimum temperatures for photosynthesis and a high minimum leaf area index needed for the forest to compete for space appear to be precursors for dieback. We then decompose the uncertainty into that associated with future climate change and that associated with forest resiliency, finding that it is important to reduce the uncertainty in both of these if we are to better determine the Amazon's outcome. © 2017 John Wiley & Sons Ltd.

Modeling urban growth by the use of a multiobjective optimization approach: environmental and economic issues for the Yangtze watershed, China.

PubMed

Zhang, Wenting; Wang, Haijun; Han, Fengxiang; Gao, Juan; Nguyen, Thuminh; Chen, Yarong; Huang, Bo; Zhan, F Benjamin; Zhou, Lequn; Hong, Song

2014-11-01

Urban growth is an unavoidable process caused by economic development and population growth. Traditional urban growth models represent the future urban growth pattern by repeating the historical urban growth regulations, which can lead to a lot of environmental problems. The Yangtze watershed is the largest and the most prosperous economic area in China, and it has been suffering from rapid urban growth from the 1970s. With the built-up area increasing from 23,238 to 31,054 km(2) during the period from 1980 to 2005, the watershed has suffered from serious nonpoint source (NPS) pollution problems, which have been mainly caused by the rapid urban growth. To protect the environment and at the same time maintain the economic development, a multiobjective optimization (MOP) is proposed to tradeoff the multiple objectives during the urban growth process of the Yangtze watershed. In particular, the four objectives of minimization of NPS pollution, maximization of GDP value, minimization of the spatial incompatibility between the land uses, and minimization of the cost of land-use change are considered by the MOP approach. Conventionally, a genetic algorithm (GA) is employed to search the Pareto solution set. In our MOP approach, a two-dimensional GA, rather than the traditional one-dimensional GA, is employed to assist with the search for the spatial optimization solution, where the land-use cells in the two-dimensional space act as genes in the GA. Furthermore, to confirm the superiority of the MOP approach over the traditional prediction approaches, a widely used urban growth prediction model, cellular automata (CA), is also carried out to allow a comparison with the Pareto solution of MOP. The results indicate that the MOP approach can make a tradeoff between the multiple objectives and can achieve an optimal urban growth pattern for Yangtze watershed, while the CA prediction model just represents the historical urban growth pattern as the future growth pattern. Moreover, according to the spatial clustering index, the urban growth pattern predicted through MOP is more reasonable. In summary, the proposed model provides a set of Pareto urban growth solutions, which compromise environmental and economic issues for the Yangtze watershed.

Estimating Demand for Industrial and Commercial Land Use Given Economic Forecasts

PubMed Central

Batista e Silva, Filipe; Koomen, Eric; Diogo, Vasco; Lavalle, Carlo

2014-01-01

Current developments in the field of land use modelling point towards greater level of spatial and thematic resolution and the possibility to model large geographical extents. Improvements are taking place as computational capabilities increase and socioeconomic and environmental data are produced with sufficient detail. Integrated approaches to land use modelling rely on the development of interfaces with specialized models from fields like economy, hydrology, and agriculture. Impact assessment of scenarios/policies at various geographical scales can particularly benefit from these advances. A comprehensive land use modelling framework includes necessarily both the estimation of the quantity and the spatial allocation of land uses within a given timeframe. In this paper, we seek to establish straightforward methods to estimate demand for industrial and commercial land uses that can be used in the context of land use modelling, in particular for applications at continental scale, where the unavailability of data is often a major constraint. We propose a set of approaches based on ‘land use intensity’ measures indicating the amount of economic output per existing areal unit of land use. A base model was designed to estimate land demand based on regional-specific land use intensities; in addition, variants accounting for sectoral differences in land use intensity were introduced. A validation was carried out for a set of European countries by estimating land use for 2006 and comparing it to observations. The models’ results were compared with estimations generated using the ‘null model’ (no land use change) and simple trend extrapolations. Results indicate that the proposed approaches clearly outperformed the ‘null model’, but did not consistently outperform the linear extrapolation. An uncertainty analysis further revealed that the models’ performances are particularly sensitive to the quality of the input land use data. In addition, unknown future trends of regional land use intensity widen considerably the uncertainty bands of the predictions. PMID:24647587

Projecting the land cover change and its environmental impacts in the Cedar River Basin in the Midwestern United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Sohl, Terry L.; Young, Claudia

2013-01-01

The physical surface of the Earth is in constant change due to climate forcing and human activities. In the Midwestern United States, urban area, farmland, and dedicated energy crop (e.g., switchgrass) cultivation are predicted to expand in the coming decades, which will lead to changes in hydrological processes. This study is designed to (1) project the land use and land cover (LULC) by mid-century using the FORecasting SCEnarios of future land-use (FORE-SCE) model under the A1B greenhouse gas emission scenario (future condition) and (2) assess its potential impacts on the water cycle and water quality against the 2001 baseline condition in the Cedar River Basin using the physically based soil and water assessment tool (SWAT). We compared the baseline LULC (National Land Cover data 2001) and 2050 projection, indicating substantial expansions of urban area and pastureland (including the cultivation of bioenergy crops) and a decrease in rangeland. We then used the above two LULC maps as the input data to drive the SWAT model, keeping other input data (e.g., climate) unchanged to isolate the LULC change impacts. The modeling results indicate that quick-response surface runoff would increase significantly (about 10.5%) due to the projected urban expansion (i.e., increase in impervious areas), and the baseflow would decrease substantially (about 7.3%) because of the reduced infiltration. Although the net effect may cause an increase in water yield, the increased variability may impede its use for public supply. Additionally, the cultivation of bioenergy crops such as switchgrass in the newly added pasture lands may further reduce the soil water content and lead to an increase in nitrogen loading (about 2.5% increase) due to intensified fertilizer application. These study results will be informative to decision makers for sustainable water resource management when facing LULC change and an increasing demand for biofuel production in this area.

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

NASA Technical Reports Server (NTRS)

Schoenenberger, Mark; Van Norman, John W.; Dyakonov, Artem A.; Karlgaard, Christopher D.; Way, David W.; Kutty, Prasad

2013-01-01

On August 5, 2012, the Mars Science Laboratory entry vehicle successfully entered Mars atmosphere, flying a guided entry until parachute deploy. The Curiosity rover landed safely in Gale crater upon completion of the Entry Descent and Landing sequence. This paper compares the aerodynamics of the entry capsule extracted from onboard flight data, including Inertial Measurement Unit (IMU) accelerometer and rate gyro information, and heatshield surface pressure measurements. From the onboard data, static force and moment data has been extracted. This data is compared to preflight predictions. The information collected by MSL represents the most complete set of information collected during Mars entry to date. It allows the separation of aerodynamic performance from atmospheric conditions. The comparisons show the MSL aerodynamic characteristics have been identified and resolved to an accuracy better than the aerodynamic database uncertainties used in preflight simulations. A number of small anomalies have been identified and are discussed. This data will help revise aerodynamic databases for future missions and will guide computational fluid dynamics (CFD) development to improved prediction codes.

The need for sustained and integrated high-resolution mapping of dynamic coastal environments

USGS Publications Warehouse

Stockdon, Hilary F.; Lillycrop, Jeff W.; Howd, Peter A.; Wozencraft, Jennifer M.

2007-01-01

The evolution of the United States' coastal zone response to both human activities and natural processes is dynamic. Coastal resource and population protection requires understanding, in detail, the processes needed for change as well as the physical setting. Sustained coastal area mapping allows change to be documented and baseline conditions to be established, as well as future behavior to be predicted in conjunction with physical process models. Hyperspectral imagers and airborne lidars, as well as other recent mapping technology advances, allow rapid national scale land use information and high-resolution elevation data collection. Coastal hazard risk evaluation has critical dependence on these rich data sets. A fundamental storm surge model parameter in predicting flooding location, for example, is coastal elevation data, and a foundation in identifying the most vulnerable populations and resources is land use maps. A wealth of information for physical change process study, coastal resource and community management and protection, and coastal area hazard vulnerability determination, is available in a comprehensive national coastal mapping plan designed to take advantage of recent mapping technology progress and data distribution, management, and collection.

Watershed sustainability: Downstream effects of timber harvest in the Ozarks of Missouri

USGS Publications Warehouse

Jacobson, Robert B.

2004-01-01

The downstream effects of timber harvest in the Ozarks of Missouri can be evaluated by analogy to other geographic areas and by historical analysis of responses to past land use activities. Based on research from other geographic regions, timber harvest in the Ozarks would be expected to have minor effects on annual water yield and dissolved-phase water quality. The potential exists for haul roads to increase stormflow discharges and sediment yields. Of the possible downstream effects, sediment yield is potentially the most severe and difficult to predict; siting and design of roads are probably the most critical management concerns for minimizing downstream effects. Historical analysis shows that Ozark streams have been destabilized by past land use practices, primarily in the riparian zone. Therefore, present-day timber harvest takes place in a landscape where streams have lowered resilience to disturbance. Predictions of future downstream effects of timber harvest in the Ozarks are complicated by the inherent complexity of cumulative watershed effects and the lack of detailed, long-term instrumental records at appropriate scales.

The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

USGS Publications Warehouse

Sohl, Terry L.; Sayler, Kristi L.; Drummond, Mark A.; Loveland, Thomas R.

2007-01-01

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

A predictive pilot model for STOL aircraft landing

NASA Technical Reports Server (NTRS)

Kleinman, D. L.; Killingsworth, W. R.

1974-01-01

An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

Simulating carbon, water and energy fluxes of a rainforest and an oil palm plantation using the Community Land Model (CLM4.5)

NASA Astrophysics Data System (ADS)

Fan, Yuanchao; Bernoux, Martial; Roupsard, Olivier; Panferov, Oleg; Le Maire, Guerric; Tölle, Merja; Knohl, Alexander

2014-05-01

Deforestation and forest degradation driven by the expansion of oil palm (Elaeis guineensis) plantations has become the major source of GHG emission in Indonesia. Changes of land surface properties (e.g. vegetation composition, soil property, surface albedo) associated with rainforest to oil palm conversion might alter the patterns of land-atmosphere energy, water and carbon cycles and therefore affect local or regional climate. Land surface modeling has been widely used to characterize the two-way interactions between climate and human disturbances on land surface. The Community Land Model (CLM) is a third-generation land model that simulates a wide range of biogeophysical and biogeochemical processes. This project utilizes the land-cover/land-use change (LCLUC) capability of the latest CLM versions 4/4.5 to characterize quantitatively how anthropogenic land surface dynamics in Indonesia affect land-atmosphere carbon, water and energy fluxes. Before simulating land use changes, the first objective is to parameterize and validate the CLM model at local rainforest and oil palm plantation sites through separate point simulations. This entails creation and parameterization of a new plant functional type (PFT) for oil palm, as well as sensitivity analysis and adaptation of model parameters for the rainforest PFTs. CLM modelled fluxes for the selected sites are to be compared with field observations from eddy covariance (EC) flux towers (e.g. a rainforest site in Bariri, Sulawesi; an oil palm site in Jambi, Sumatra). After validation, the project will proceed to parameterize land-use transformation system using remote sensing data and to simulate the impacts of historical LUCs on carbon, water and energy fluxes. Last but not least, the effects of future LUCs in Indonesia on the fluxes and carbon sequestration capacity will be investigated through scenario study. Historical land cover changes, especially oil palm coverage, are retrieved from Landsat or MODIS archival images. Oil palm concession boundaries are used to define and project future land use scenarios. Initial results include outputs from a single-point simulation for the Bariri rainforest site forced with locally measured meteorological data which already showed significant advantage over global forcing data in predicting net ecosystem exchange and latent and sensible heat fluxes. Modeled fluxes are being compared with EC flux observations and with Mixfor-SVAT model outputs from another project at the same site. In the next few months, focus will be on sensitivity analyses of model parameters including PFT optical, morphological and physiological parameters that are necessary to configure the new oil palm PFT and represent rainforest to oil palm conversion. The new parameterization will contribute to the development of the CLM model and its implementation in the modelling of LUC effects in tropical regions will help understanding land-climate interactions.

Estimation of Land Surface Temperature for the Quantitative Analysis of Land Cover of Lower Areas of Sindh to Assess the Impacts of Climate Variability

NASA Astrophysics Data System (ADS)

Qaisar, Maha

2016-07-01

Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded that transitory alteration of the biophysical characteristics of the surface driven by variations in rainfall is the prevailing progression. Moreover, future work will focus on finer-scale analysis and validations of patterns of changes due to rapid urbanization and population explosion in poverty stricken areas of Sindh which are posing an adverse impact on the land utilization and in turn increasing the land surface temperature and ultimately more stress on the low lying areas of Sindh i.e. Indus Delta will be losing its productivity and capacity to bear biodiversity whether the fauna or flora. Hence, this regional scale problem will become a global concern. Therefore, it is needed to stop the menace in its starting phase to mitigate the problem and to bring minds on this horrendous situation.

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Land use in Maine: determinants of past trends and projections of future changes.

Treesearch

Andrew J. Plantinga; Thomas Mauldlin; Ralph J. Alig

1999-01-01

About 90 percent of the land in Maine is in forests. We analyzed past land use trends in Maine and developed projections of future land use. Since the 1950s, the area of forest in Maine has increased by almost 400,000 acres; however, the trends differ among ownerships, as the area of nonindustrial private timberland declined by 800,000 acres since 1950, while private...

Quantifying the effect of nighttime interactions between roots and canopy physiology and their control of water and carbon cycling on feedbacks between soil moisture and terrestrial climatology under variable environmental conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Domec, Jean-Christophe; Palmroth, Sari; Oren, Ram

The primary objective of this project is to characterize and quantify how the temporal variability of hydraulic redistribution (HR) and its physiological regulation in unmanaged and complex forests is affecting current water and carbon exchange and predict how future climate scenarios will affect these relationships and potentially feed back to the climate. Specifically, a detailed study of ecosystem water uptake and carbon exchange in relation to root functioning was proposed in order to quantify the mechanisms controlling temporal variability of soil moisture dynamic and HR in three active AmeriFlux sites, and to use published data of two other inactive AmeriFluxmore » sites. Furthermore, data collected by our research group at the Duke Free Air CO2 enrichment (FACE) site was also being utilized to further improve our ability to forecast future environmental impacts of elevated CO2 concentration on soil moisture dynamic and its effect on carbon sequestration and terrestrial climatology. The overarching objective being to forecast, using a soil:plant:atmosphere model coupled with a biosphere:atmosphere model, the impact of root functioning on land surface climatology. By comparing unmanaged sites to plantations, we also proposed to determine the effect of land use change on terrestrial carbon sequestration and climatology through its effect on soil moisture dynamic and HR. Our simulations of HR by roots indicated that in some systems HR is an important mechanism that buffers soil water deficit, affects energy and carbon cycling; thus having significant implications for seasonal climate. HR maintained roots alive and below 70% loss of conductivity and our simulations also showed that the increased vapor pressure deficit at night under future conditions was sufficient to drive significant nighttime transpiration at all sites, which reduced HR. This predicted reduction in HR under future climate conditions played an important regulatory role in land atmosphere interactions by affecting whole ecosystem carbon and water balance. Under future climatic scenarios, HR was reduced thus affecting negatively plant water use and carbon assimilation. The discrepancy between the predicted and actual surface warming and atmospheric water vapor caused by the persistence of evapotranspiration during the dry season, increasing energy transfer in the form of latent heat. Under those simulations, we also evaluated how the hydraulic properties of soil and xylem limited the rate of carbon uptake, and carbon net ecosystem exchange. The multilayered hydraulically driven soil vegetation atmosphere carbon and water transfer model was designed to represent processes common to vascular plants, so that ecosystem atmosphere exchange could be captured by the same processes at different sites. Those models shown to be well suited for investigating the impact of drought on forest ecosystems because of its explicit treatment of water transport to leaves. This modeling work also confirmed that unmanaged, mixed hardwood site are more resilient to climatic variations than an adjacent pine plantation, but that future climatic conditions will reverse this trends.« less

Evaluating the impacts of climate and land-use change on the hydrology and nutrient yield in a transboundary river basin: A case study in the 3S River Basin (Sekong, Sesan, and Srepok).

PubMed

Trang, Nguyen Thi Thuy; Shrestha, Sangam; Shrestha, Manish; Datta, Avishek; Kawasaki, Akiyuki

2017-01-15

Assessment of the climate and land-use change impacts on the hydrology and water quality of a river basin is important for the development and management of water resources in the future. The objective of this study was to examine the impact of climate and land-use change on the hydrological regime and nutrient yield from the 3S River Basin (Sekong, Srepok, and Sesan) into the 3S River system in Southeast Asia. The 3S Rivers are important tributaries of the Lower Mekong River, accounting for 16% of its annual flow. This transboundary basin supports the livelihoods of nearly 3.5 million people in the countries of Laos, Vietnam, and Cambodia. To reach a better understanding of the process and fate of pollution (nutrient yield) as well as the hydrological regime, the Soil and Water Assessment Tool (SWAT) was used to simulate water quality and discharge in the 3S River Basin. Future scenarios were developed for three future periods: 2030s (2015-2039), 2060s (2045-2069), and 2090s (2075-2099), using an ensemble of five GCMs (General Circulation Model) simulations: (HadGEM2-AO, CanESM2, IPSL-CM5A-LR, CNRM-CM5, and MPI-ESM-MR), driven by the climate projection for RCPs (Representative Concentration Pathways): RCP4.5 (medium emission) and RCP8.5 (high emission) scenarios, and two land-use change scenarios. The results indicated that the climate in the study area would generally become warmer and wetter under both emission scenarios. Discharge and nutrient yield is predicted to increase in the wet season and decrease in the dry. Overall, the annual discharge and nutrient yield is projected to increase throughout the twenty-first century, suggesting sensitivity in the 3S River Basin to climate and land-use change. The results of this study can assist water resources managers and planners in developing water management strategies for uncertain climate change scenarios in the 3S River Basin. Copyright © 2016 Elsevier B.V. All rights reserved.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

The UKC2 regional coupled environmental prediction system

NASA Astrophysics Data System (ADS)

Lewis, Huw W.; Castillo Sanchez, Juan Manuel; Graham, Jennifer; Saulter, Andrew; Bornemann, Jorge; Arnold, Alex; Fallmann, Joachim; Harris, Chris; Pearson, David; Ramsdale, Steven; Martínez-de la Torre, Alberto; Bricheno, Lucy; Blyth, Eleanor; Bell, Victoria A.; Davies, Helen; Marthews, Toby R.; O'Neill, Clare; Rumbold, Heather; O'Dea, Enda; Brereton, Ashley; Guihou, Karen; Hines, Adrian; Butenschon, Momme; Dadson, Simon J.; Palmer, Tamzin; Holt, Jason; Reynard, Nick; Best, Martin; Edwards, John; Siddorn, John

2018-01-01

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.

Modeling Future Land Use Scenarios in South Korea: Applying the IPCC Special Report on Emissions Scenarios and the SLEUTH Model on a Local Scale

NASA Astrophysics Data System (ADS)

Han, Haejin; Hwang, YunSeop; Ha, Sung Ryong; Kim, Byung Sik

2015-05-01

This study developed three scenarios of future land use/land cover on a local level for the Kyung-An River Basin and its vicinity in South Korea at a 30-m resolution based on the two scenario families of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES): A2 and B1, as well as a business-as-usual scenario. The IPCC SRES A2 and B1 were used to define future local development patterns and associated land use change. We quantified the population-driven demand for urban land use for each qualitative storyline and allocated the urban demand in geographic space using the SLEUTH model. The model results demonstrate the possible land use/land cover change scenarios for the years from 2000 to 2070 by examining the broad narrative of each SRES within the context of a local setting, such as the Kyoungan River Basin, constructing narratives of local development shifts and modeling a set of `best guess' approximations of the future land use conditions in the study area. This study found substantial differences in demands and patterns of land use changes among the scenarios, indicating compact development patterns under the SRES B1 compared to the rapid and dispersed development under the SRES A2.

Modeling future land use scenarios in South Korea: applying the IPCC special report on emissions scenarios and the SLEUTH model on a local scale.

PubMed

Han, Haejin; Hwang, YunSeop; Ha, Sung Ryong; Kim, Byung Sik

2015-05-01

This study developed three scenarios of future land use/land cover on a local level for the Kyung-An River Basin and its vicinity in South Korea at a 30-m resolution based on the two scenario families of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES): A2 and B1, as well as a business-as-usual scenario. The IPCC SRES A2 and B1 were used to define future local development patterns and associated land use change. We quantified the population-driven demand for urban land use for each qualitative storyline and allocated the urban demand in geographic space using the SLEUTH model. The model results demonstrate the possible land use/land cover change scenarios for the years from 2000 to 2070 by examining the broad narrative of each SRES within the context of a local setting, such as the Kyoungan River Basin, constructing narratives of local development shifts and modeling a set of 'best guess' approximations of the future land use conditions in the study area. This study found substantial differences in demands and patterns of land use changes among the scenarios, indicating compact development patterns under the SRES B1 compared to the rapid and dispersed development under the SRES A2.

Predictor symbology in computer-generated pictorial displays

NASA Technical Reports Server (NTRS)

Grunwald, A. J.

1981-01-01

The display under investigation, is a tunnel display for the four-dimensional commercial aircraft approach-to-landing under instrument flight rules. It is investigated whether more complex predictive information such as a three-dimensional perspective vehicle symbol, predicting the future vehicle position as well as future vehicle attitude angles, contributes to a better system response, and suitable predictor laws for the predictor motions, are formulated. Methods for utilizing the predictor symbol in controlling the forward velocity of the aircraft in four-dimensional approaches, are investigated. The simulator tests show, that the complex perspective vehicle symbol yields improved damping in the lateral response as compared to a flat two-dimensional predictor cross, but yields generally larger vertical deviations. Methods of using the predictor symbol in controlling the forward velocity of the vehicle are shown to be effective. The tunnel display with superimposed perspective vehicle symbol yields very satisfactory results and pilot acceptance in the lateral control but is found to be unsatisfactory in the vertical control, as a result of too large vertical path-angle deviations.

Opportunities and challenges of sustainable agricultural development in China.

PubMed

Zhao, Jingzhu; Luo, Qishan; Deng, Hongbing; Yan, Yan

2008-02-27

This paper introduces the concepts and aims of sustainable agriculture in China. Sustainable agricultural development comprises sustainability of agricultural production, sustainability of the rural economy, ecological and environmental sustainability within agricultural systems and sustainability of rural society. China's prime aim is to ensure current and future food security. Based on projections of China's population, its economy, societal factors and agricultural resources and inputs between 2000 and 2050, total grain supply and demand has been predicted and the state of food security analysed. Total and per capita demand for grain will increase continuously. Total demand will reach 648 Mt in 2020 and 700 Mt in 2050, while total grain yield of cultivated land will reach 470 Mt in 2010, 585 Mt in 2030 and 656 Mt in 2050. The per capita grain production will be around 360kg in the period 2000-2030 and reach 470kg in 2050. When productivities of cultivated land and other agricultural resources are all taken into consideration, China's food self-sufficiency ratio will increase from 94.4% in 2000 to 101.3% in 2030, suggesting that China will meet its future demand for food and need for food security. Despite this positive assessment, the country's sustainable agricultural development has encountered many obstacles. These include: agricultural water-use shortage; cultivated land loss; inappropriate usage of fertilizers and pesticides, and environmental degradation.

Significance of hydrological model choice and land use changes when doing climate change impact assessment

NASA Astrophysics Data System (ADS)

Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

2014-05-01

Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the quantification of the effects of climate change on hydrological response." Climate Change 35: 415-434. Hewitt, C. D. and D. J. Griggs (2004). "Ensembles-based predictions of climate changes and their impacts." Eos, Transactions American Geophysical Union 85: 1-566. Jiang, T., Y. D. Chen, C. Xu, X. Chen, X. Chen and V. P. Singh (2007). "Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China." Journal of hydrology 336: 316-333. Refsgaard, J. C., K. Arnbjerg-Nielsen, M. Drews, K. Halsnæs, E. Jeppesen, H. Madsen, A. Markandya, J. E. Olesen, J. R. Porter and J. H. Christensen (2013). "The role of uncertainty in climate change adaptation strategies - A Danish water management example." Mitigation and Adaptation Strategies for Global Change 18: 337-359.

The interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

Marshall, Leon; Biesmeijer, Jacobus C; Rasmont, Pierre; Vereecken, Nicolas J; Dvorak, Libor; Fitzpatrick, Una; Francis, Frédéric; Neumayer, Johann; Ødegaard, Frode; Paukkunen, Juho P T; Pawlikowski, Tadeusz; Reemer, Menno; Roberts, Stuart P M; Straka, Jakub; Vray, Sarah; Dendoncker, Nicolas

2018-01-01

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Modelling nitrate from land-surface to wells-perforations under Mediterranean agricultural land: success, failure, and future scenarios

NASA Astrophysics Data System (ADS)

Levy, Yehuda; Chefetz, Benny; Shapira, Roi; Kurtzman, Daniel

2017-04-01

Contamination of groundwater resources by nitrate due to leaching under agricultural land is probably the most troublesome agriculture-related water contamination, worldwide. Deep soil sampling (10 m) were used for calibrating vertical flow and nitrogen-transport numerical models of the unsaturated zone, under different agricultural land uses. Vegetables fields (potato and strawberries) and deciduous (persimmon) orchards in the Sharon area overlaying the coastal aquifer of Israel, were examined. Average nitrate-nitrogen fluxes below vegetables fields were 210-290 kg ha-1 a-1 and under deciduous orchards were 110-140 kg ha-1 a-1. The output water and nitrate-nitrogen fluxes of the unsaturated zone models were used as input for a three dimensional flow and nitrate-transport model in the aquifer under an area of 13.3 square kilometers of agricultural land. The area was subdivided to 4 agricultural land-uses: vegetables, deciduous, citrus orchards and non-cultivated. Fluxes of water and nitrate-nitrogen below citrus orchards were taken from a previous study in this area (Kurtzman et al., 2013, j. Contam. Hydrol.). The groundwater flow model was calibrated to well heads only by changing the hydraulic conductivity while transient recharge fluxes were constraint to the bottom-fluxes of the unsaturated zone flow models. The nitrate-transport model in the aquifer, which was fed at the top by the nitrate fluxes of the unsaturated zone models, succeeded in reconstructing the average nitrate concentration in the wells. On the other hand, this transport model failed in calculating the high concentrations in the most contaminated wells and the large spatial variability of nitrate-concentrations in the aquifer. In order to reconstruct the spatial variability and enable predictions nitrate-fluxes from the unsaturated zone were multiplied by local multipliers. This action was rationalized by the fact that the high concentrations in some wells cannot be explained by regular agricultural activity, and are probably a result of some malfunction in the well area. Prediction of the nitrate concentration 40 years to the future with 3 nitrogen-fertilization scenarios showed the following: 1) under "business as usual" fertilization scenario, the NO3 concentration will increase in average by 19 mg l-1; 2) In reducing 25% of the nitrogen fertilization mass scenario, the nitrate concentration in the aquifer will stabilize; 3) In reducing 50% of the nitrogen fertilization mass scenario, the concentration will decrease in average by 18 mg l-1.

Adapting the Biome-BGC Model to New Zealand Pastoral Agriculture: Climate Change and Land-Use Change

NASA Astrophysics Data System (ADS)

Keller, E. D.; Baisden, W. T.; Timar, L.

2011-12-01

We have adapted the Biome-BGC model to make climate change and land-use scenario estimates of New Zealand's pasture production in 2020 and 2050, with comparison to a 2005 baseline. We take an integrated modelling approach with the aim of enabling the model's use for policy assessments across broadly related issues such as climate change mitigation and adaptation, land-use change, and greenhouse gas projections. The Biome-BGC model is a biogeochemical model that simulates carbon, water, and nitrogen cycles in terrestrial ecosystems. We introduce two new 'ecosystems', sheep/beef and dairy pasture, within the existing structure of the Biome-BGC model and calibrate its ecophysiological parameters against pasture clipping data from diverse sites around New Zealand to form a baseline estimate of total New Zealand pasture production. Using downscaled AR4 climate projections, we construct mid- and upper-range climate change scenarios in 2020 and 2050. We produce land-use change scenarios in the same years by combining the Biome-BGC model with the Land Use in Rural New Zealand (LURNZ) model. The LURNZ model uses econometric approaches to predict future land-use change driven by changes in net profits driven by expected pricing, including the introduction of an emission trading system. We estimate the relative change in national pasture production from our 2005 baseline levels for both sheep/beef and dairy systems under each scenario.

Effects of climate change and seed dispersal on airborne ragweed pollen loads in Europe

NASA Astrophysics Data System (ADS)

Hamaoui-Laguel, Lynda; Vautard, Robert; Liu, Li; Solmon, Fabien; Viovy, Nicolas; Khvorostyanov, Dmitry; Essl, Franz; Chuine, Isabelle; Colette, Augustin; Semenov, Mikhail A.; Schaffhauser, Alice; Storkey, Jonathan; Thibaudon, Michel; Epstein, Michelle M.

2015-08-01

Common ragweed (Ambrosia artemisiifolia) is an invasive alien species in Europe producing pollen that causes severe allergic disease in susceptible individuals. Ragweed plants could further invade European land with climate and land-use changes. However, airborne pollen evolution depends not only on plant invasion, but also on pollen production, release and atmospheric dispersion changes. To predict the effect of climate and land-use changes on airborne pollen concentrations, we used two comprehensive modelling frameworks accounting for all these factors under high-end and moderate climate and land-use change scenarios. We estimate that by 2050 airborne ragweed pollen concentrations will be about 4 times higher than they are now, with a range of uncertainty from 2 to 12 largely depending on the seed dispersal rate assumptions. About a third of the airborne pollen increase is due to on-going seed dispersal, irrespective of climate change. The remaining two-thirds are related to climate and land-use changes that will extend ragweed habitat suitability in northern and eastern Europe and increase pollen production in established ragweed areas owing to increasing CO2. Therefore, climate change and ragweed seed dispersal in current and future suitable areas will increase airborne pollen concentrations, which may consequently heighten the incidence and prevalence of ragweed allergy.

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

Modeling the Acceleration of Global Surface Temperture

NASA Astrophysics Data System (ADS)

Jones, B.

2017-12-01

A mathematical projection focusing on the changing rate of acceleration of Global Surface Temperatures. Using historical trajectory and informed expert near-term prediction, it is possible to extend this further forward drawing a reference arc of acceleration. Presented here is an example of this technique based on data found in the Summary of Findings of A New Estimate of the Average Earth Surface Land Temperature Spanning 1753 to 2011 and that same team's stated prediction to 2050. With this, we can project a curve showing future acceleration: Decade (midpoint) Change in Global Land Temp Degrees C Known Slope Projected Trend 1755 0.000 1955 0.600 0.0030 2005 1.500 0.0051 2045 3.000 0.0375 2095 5.485 0.0497 2145 8.895 0.0682 2195 13.488 0.0919 Observations: Slopes are getting steeper and doing so faster in an "acceleration of the acceleration" or an "arc of acceleration". This is consistent with the non-linear accelerating feedback loops of global warming. Such projected temperatures threaten human civilization and human life. This `thumbnail' projection is consistent with the other long term predictions based on anthropogenic greenhouse gases. This projection is low when compared to those whose forecasts include greenhouse gases released from thawing permafrost and clathrate hydrates. A reference line: This curve should be considered a point of reference. In the near term and absent significant drawdown of greenhouse gases, my "bet" for this AGU session is that future temperatures will generally be above this reference curve. For example, the decade ending 2020 - more than 1.9C and the decade ending 2030 - more than 2.3C - again measured from the 1750 start point. *Caveat: The long term curve and prediction assumes that mankind does not move quickly away from high cost fossil fuels and does not invent, mobilize and take actions drawing down greenhouse gases. Those seeking a comprehensive action plan are directed to drawdown.org

Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: a case study in North Dakota, USA.

PubMed

Li, Ruopu; Merchant, James W

2013-03-01

Modeling groundwater vulnerability to pollution is critical for implementing programs to protect groundwater quality. Most groundwater vulnerability modeling has been based on current hydrogeology and land use conditions. However, groundwater vulnerability is strongly dependent on factors such as depth-to-water, recharge and land use conditions that may change in response to future changes in climate and/or socio-economic conditions. In this research, a modeling framework, which employs three sets of models linked within a geographic information system (GIS) environment, was used to evaluate groundwater pollution risks under future climate and land use changes in North Dakota. The results showed that areas with high vulnerability will expand northward and/or northwestward in Eastern North Dakota under different scenarios. GIS-based models that account for future changes in climate and land use can help decision-makers identify potential future threats to groundwater quality and take early steps to protect this critical resource. Copyright © 2013 Elsevier B.V. All rights reserved.

Failure to use corollary discharge to remap visual target locations is associated with psychotic symptom severity in schizophrenia

PubMed Central

Rösler, Lara; Rolfs, Martin; van der Stigchel, Stefan; Neggers, Sebastiaan F. W.; Cahn, Wiepke; Kahn, René S.

2015-01-01

Corollary discharge (CD) refers to “copies” of motor signals sent to sensory areas, allowing prediction of future sensory states. They enable the putative mechanisms supporting the distinction between self-generated and externally generated sensations. Accordingly, many authors have suggested that disturbed CD engenders psychotic symptoms of schizophrenia, which are characterized by agency distortions. CD also supports perceived visual stability across saccadic eye movements and is used to predict the postsaccadic retinal coordinates of visual stimuli, a process called remapping. We tested whether schizophrenia patients (SZP) show remapping disturbances as evidenced by systematic transsaccadic mislocalizations of visual targets. SZP and healthy controls (HC) performed a task in which a saccadic target disappeared upon saccade initiation and, after a brief delay, reappeared at a horizontally displaced position. HC judged the direction of this displacement accurately, despite spatial errors in saccade landing site, indicating that their comparison of the actual to predicted postsaccadic target location relied on accurate CD. SZP performed worse and relied more on saccade landing site as a proxy for the presaccadic target, consistent with disturbed CD. This remapping failure was strongest in patients with more severe psychotic symptoms, consistent with the theoretical link between disturbed CD and phenomenological experiences in schizophrenia. PMID:26108951

Evaluation and Analysis of Eco-Security in Environmentally Sensitive Areas Using an Emergy Ecological Footprint.

PubMed

Chen, Han-Shen

2017-01-30

In this paper, the overall ecological and environmental sustainability in the Cing-Jing region in Taiwan is examined. As land use and cover change has been found to be an important analysis method, an emergy ecological footprint model was applied and the eco-security assessed to ensure authorities maintain a balance between ecological preservation and tourism development. While the ecological environment in the Cing-Jing region from 2008 to 2014 was found to be within safe levels, all related indices had increased considerably. A Grey model was used to predict the 2015-2024 ecological carrying capacities, from which it was found that there is expected to be a large increase in per capita ecological footprints (EFs), meaning that in the future there is going to be a larger ecological deficit and a higher ecological pressure index (EFI), with the eco-security predicted to reach a Grade 2 intermediate level in 2022. As the Cing-Jing region is predicted to become ecologically unsustainable, local, regional, and national governments need to implement regulations to strictly control the land use in the Cing-Jing region. This study demonstrated that emergy EF (EEF) theory application can give objective guidance to decision-makers to ensure that recreational non-urban eco-security can be maintained at a safe level.

Evaluation and Analysis of Eco-Security in Environmentally Sensitive Areas Using an Emergy Ecological Footprint

PubMed Central

Chen, Han-Shen

2017-01-01

In this paper, the overall ecological and environmental sustainability in the Cing-Jing region in Taiwan is examined. As land use and cover change has been found to be an important analysis method, an emergy ecological footprint model was applied and the eco-security assessed to ensure authorities maintain a balance between ecological preservation and tourism development. While the ecological environment in the Cing-Jing region from 2008 to 2014 was found to be within safe levels, all related indices had increased considerably. A Grey model was used to predict the 2015–2024 ecological carrying capacities, from which it was found that there is expected to be a large increase in per capita ecological footprints (EFs), meaning that in the future there is going to be a larger ecological deficit and a higher ecological pressure index (EFI), with the eco-security predicted to reach a Grade 2 intermediate level in 2022. As the Cing-Jing region is predicted to become ecologically unsustainable, local, regional, and national governments need to implement regulations to strictly control the land use in the Cing-Jing region. This study demonstrated that emergy EF (EEF) theory application can give objective guidance to decision-makers to ensure that recreational non-urban eco-security can be maintained at a safe level. PMID:28146086

Distributed Hydrologic Modeling of Semiarid Basins in Arizona: A Platform for Land Cover and Climate Change Assessments

NASA Astrophysics Data System (ADS)

Hawkins, G. A.; Vivoni, E. R.

2011-12-01

Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision-making under the uncertainties induced by combined climate and land cover change.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development.

PubMed

Porter, Kenneth D H; Reaney, Sim M; Quilliam, Richard S; Burgess, Chris; Oliver, David M

2017-12-31

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r s =0.88; p<0.01) than the Wyre (r s =-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

ASSESSING THE RELATIVE AND COMBINED IMPACTS OF FUTURE LAND-USE AND CLIMATE CHANGES ON NONPOINT SOURCE POLLUTION

EPA Science Inventory

In this paper, we discuss the potential water quality impacts of future land-use and climate changes. The Little Miami River Basin was used as a case study. It is a predominantly agricultural watershed in southwestern Ohio (U.S.A.) that has experienced land-use modifications. ...

Deforestation scenarios for the Bolivian lowlands.

PubMed

Tejada, Graciela; Dalla-Nora, Eloi; Cordoba, Diana; Lafortezza, Raffaele; Ovando, Alex; Assis, Talita; Aguiar, Ana Paula

2016-01-01

Tropical forests in South America play a key role in the provision of ecosystem services such as carbon sinks, biodiversity conservation, and global climate regulation. In previous decades, Bolivian forests have mainly been deforested by the expansion of agricultural frontier development, driven by the growing demands for beef and other productions. In the mid-2000s the Movimiento al Socialismo (MAS) party rose to power in Bolivia with the promise of promoting an alternative development model that would respect the environment. The party passed the world's first laws granting rights to the environment, which they termed Mother Earth (Law No. 300 of 2012), and proposed an innovative framework that was expected to develop radical new conservation policies. The MAS conservationist discourse, policies, and productive practices, however, have since been in permanent tension. The government continues to guarantee food production through neo-extractivist methods by promoting the notion to expand agriculture from 3 to 13 million ha, risking the tropical forests and their ecosystem services. These actions raise major environmental and social concerns, as the potential impacts of such interventions are still unknown. The objective of this study is to explore an innovative land use modeling approach to simulate how the growing demand for land could affect future deforestation trends in Bolivia. We use the LuccME framework to create a spatially-explicit land cover change model and run it under three different deforestation scenarios, spanning from the present-2050. In the Sustainability scenario, deforestation reaches 17,703,786 ha, notably in previously deforested or degraded areas, while leaving forest extensions intact. In the Middle of the road scenario, deforestation and degradation move toward new or paved roads spreading across 25,698,327 ha in 2050, while intact forests are located in Protected Areas (PAs). In the Fragmentation scenario, deforestation expands to almost all Bolivian lowlands reaching 37,944,434 ha and leaves small forest patches in a few PAs. These deforestation scenarios are not meant to predict the future but to show how current and future decisions carried out by the neo-extractivist practices of MAS government could affect deforestation and carbon emission trends. In this perspective, recognizing land use systems as open and dynamic systems is a central challenge in designing efficient land use policies and managing a transition towards sustainable land use. Copyright © 2015 Elsevier Inc. All rights reserved.

Impacts of Biofuel-Induced Agricultural Land Use Changes on Watershed Hydrology and Water Quality

NASA Astrophysics Data System (ADS)

Lin, Z.; Zheng, H.

2015-12-01

The US Energy Independence and Security Act (EISA) of 2007 has contributed to widespread changes in agricultural land uses. The impact of these land use changes on regional water resources could also be significant. Agricultural land use changes were evaluated for the Red River of the North Basin (RRNB), an international river basin shared by the US and Canada. The influence of the land use changes on spring snowmelt flooding and downstream water quality was also assessed using watershed modeling. The planting areas for corn and soybean in the basin increased by 62% and 18%, while those for spring wheat, forest, and pasture decreased by 30%, 18%, and 50%, from 2006 to 2013. Although the magnitude of spring snowmelt peak flows in the Red River did not change from pre-EISA to post-EISA, our uncertainty analysis of the normalized hydrographs revealed that the downstream streamflows had a greater variability under the post-EISA land use scenario, which may lead to greater uncertainty in predicting spring snowmelt floods in the Red River. Hydrological simulation also showed that the sediment and nutrient loads at the basin's outlet in the US and Canada border increased under the post-EISA land use scenario, on average sediment increasing by 2.6%, TP by 14.1%, nitrate nitrogen by 5.9%, and TN by 9.1%. Potential impacts of the future biofuel crop scenarios on watershed hydrology and water quality in the RRNB were also simulated through integrated economic-hydrologic modeling.

Exploring Agricultural Livelihood Transitions with an Agent-Based Virtual Laboratory: Global Forces to Local Decision-Making

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2013-01-01

Rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change. A primary challenge is, thus, to explain these shifts in terms of the actors and processes operating within a variety of land systems in order to understand how land users might respond locally to future changes in broader-scale environmental and economic conditions. Using ‘induced intensification’ theory as a benchmark, we develop a generalized agent-based model to investigate mechanistic explanations of relationships between agricultural intensity and population density, environmental suitability, and market influence. Land-use and livelihood decisions modeled from basic micro-economic theories generated spatial and temporal patterns of agricultural intensification consistent with predictions of induced intensification theory. Further, agent actions in response to conditions beyond those described by induced intensification theory were explored, revealing that interactions among environmental constraints, population pressure, and market influence may produce transitions to multiple livelihood regimes of varying market integration. The result is new hypotheses that could modify and enrich understanding of the classic relationship between agricultural intensity and population density. The strength of this agent-based model and the experimental results is the generalized form of the decision-making processes underlying land-use and livelihood transitions, creating the prospect of a virtual laboratory for systematically generating hypotheses of how agent decisions and interactions relate to observed land-use and livelihood patterns across diverse land systems. PMID:24039892

Defining, Measuring, and Incentivizing Sustainable Land Use to Meet Human Needs

NASA Astrophysics Data System (ADS)

Nicholas, K. A.; Brady, M. V.; Olin, S.; Ekroos, J.; Hall, M.; Seaquist, J. W.; Lehsten, V.; Smith, H.

2016-12-01

Land is a natural capital that supports the flow of an enormous amount of ecosystem services critical to human welfare. Sustainable land use, which we define as land use that meets both current and future human needs for ecosystem services, is essential to meet global goals for climate mitigation and sustainable development, while maintaining natural capital. However, it is not clear what governance is needed to achieve sustainable land use under multiple goals (as defined by the values of relevant decision-makers and land managers), particularly under climate change. Here we develop a conceptual model for examining the interactions and tradeoffs among multiple goals, as well as their spatial interactions (teleconnections), in research developed using Design Thinking principles. We have selected five metrics for provisioning (food production, and fiber production for wood and energy), regulating and maintenance (climate mitigation and biodiversity conservation), and cultural (heritage) ecosystem services. Using the case of Sweden, we estimate indicators for these metrics using a combination of existing data synthesis and process-based simulation modeling. We also develop and analyze new indicators (e.g., combining data on land use, bird conservation status, and habitat specificity to make a predictive model of bird diversity changes on agricultural or forested land). Our results highlight both expected tradeoffs (e.g., between food production and biodiversity conservation) as well as unexpected opportunities for synergies under different land management scenarios and strategies. Our model also provides a practical way to make decision-maker values explicit by comparing both quantity and preferences for bundles of ecosystem services under various scenarios. We hope our model will help in considering competing interests and shaping economic incentives and governance structures to meet national targets in support of global goals for sustainable management of land-based ecosystem services.

Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative

NASA Astrophysics Data System (ADS)

Frank, Dorothea; Reichstein, Markus

2017-04-01

The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.

Coupling of Markov chains and cellular automata spatial models to predict land cover changes (case study: upper Ci Leungsi catchment area)

NASA Astrophysics Data System (ADS)

Marko, K.; Zulkarnain, F.; Kusratmoko, E.

2016-11-01

Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.

Assessing Land Management Change Effects on Forest Carbon and Emissions Under Changing Climate

NASA Astrophysics Data System (ADS)

Law, B. E.

2014-12-01

There has been limited focus on fine-scale land management change effects on forest carbon under future environmental conditions (climate, nitrogen deposition, increased atmospheric CO2). Forest management decisions are often made at the landscape to regional levels before analyses have been conducted to determine the potential outcomes and effectiveness of such actions. Scientists need to evaluate plausible land management actions in a timely manner to help shape policy and strategic land management. Issues of interest include species-level adaptation to climate, resilience and vulnerability to mortality within forested landscapes and regions. Efforts are underway to improve land system model simulation of future mortality related to climate, and to develop and evaluate plausible land management options that could help mitigate or avoid future die-offs. Vulnerability to drought-related mortality varies among species and with tree size or age. Predictors of species ability to survive in specific environments are still not resolved. A challenge is limited observations for fine-scale (e.g. 4 km2) modeling, particularly physiological parameters. Uncertainties are primarily associated with future land management and policy decisions. They include the interface with economic factors and with other ecosystem services (biodiversity, water availability, wildlife habitat). The outcomes of future management scenarios should be compared with business-as-usual management under the same environmental conditions to determine the effects of management changes on forest carbon and net emissions to the atmosphere. For example, in the western U.S., land system modeling and life cycle assessment of several management options to reduce impacts of fire reduced long-term forest carbon gain and increased carbon emissions compared with business-as-usual management under future environmental conditions. The enhanced net carbon uptake with climate and reduced fire emissions after thinning did not compensate for the increased wood removals over 90 years, leading to reduced net biome production. Analysis of land management change scenarios at fine scales is needed, and should consider other ecological values in addition to carbon.

A global assessment of gross and net land change dynamics for current conditions and future scenarios

NASA Astrophysics Data System (ADS)

Fuchs, Richard; Prestele, Reinhard; Verburg, Peter H.

2018-05-01

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5° grid cells was substantially larger than net changes in all parts of the world. As 0.5° grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

Analysis of Future Streamflow Regimes under Global Change Scenarios in Central Chile for Ecosystem Sustainability

NASA Astrophysics Data System (ADS)

Henriquez Dole, L. E.; Gironas, J. A.; Vicuna, S.

2015-12-01

Given the critical role of the streamflow regime for ecosystem sustainability, modeling long term effects of climate change and land use change on streamflow is important to predict possible impacts in stream ecosystems. Because flow duration curves are largely used to characterize the streamflow regime and define indices of ecosystem health, they were used to represent and analyze in this study the stream regime in the Maipo River Basin in Central Chile. Water and Environmental Assessment and Planning (WEAP) model and the Plant Growth Model (PGM) were used to simulate water distribution, consumption in rural areas and stream flows on a weekly basis. Historical data (1990-2014), future land use scenarios (2030/2050) and climate change scenarios were included in the process. Historical data show a declining trend in flows mainly by unprecedented climatic conditions, increasing interest among users on future streamflow scenarios. In the future, under an expected decline in water availability coupled with changes in crop water demand, water users will be forced to adapt by changing water allocation rules. Such adaptation actions would in turns affect the streamflow regime. Future scenarios for streamflow regime show dramatic changes in water availability and temporal distribution. Annual weekly mean flows can reduce in 19% in the worst scenario and increase in 3.3% in the best of them, and variability in streamflow increases nearly 90% in all scenarios under evaluation. The occurrence of maximum and minimum monthly flows changes, as June instead of July becomes the driest month, and December instead of January becomes the month with maximum flows. Overall, results show that under future scenarios streamflow is affected and altered by water allocation rules to satisfy water demands, and thus decisions will need to consider the streamflow regime (and habitat) in order to be sustainable.

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thornton, Peter E.; Calvin, Katherine; Jones, Andrew D.

Fossil fuel combustion and land-use change are the first and second largest contributors to industrial-era increases in atmospheric carbon dioxide concentration, which is itself the largest driver of present-day climate change1. Projections of fossil fuel consumption and land-use change are thus fundamental inputs for coupled Earth system models (ESM) used to estimate the physical and biological consequences of future climate system forcing2,3. While empirical datasets are available to inform historical analyses4,5, assessments of future climate change have relied on projections of energy and land use based on energy economic models, constrained using historical and present-day data and forced with assumptionsmore » about future policy, land-use patterns, and socio-economic development trajectories6. Here we show that the influence of biospheric change – the integrated effect of climatic, ecological, and geochemical processes – on land ecosystems has a significant impact on energy, agriculture, and land-use projections for the 21st century. Such feedbacks have been ignored in previous ESM studies of future climate. We find that synchronous exposure of land ecosystem productivity in the economic system to biospheric change as it develops in an ESM results in a 10% reduction of land area used for crop cultivation; increased managed forest area and land carbon; a 15-20% decrease in global crop price; and a 17% reduction in fossil fuel emissions for a low-mid range forcing scenario7. These simulation results demonstrate that biospheric change can significantly alter primary human system forcings to the climate system. This synchronous two-way coupling approach removes inconsistencies in description of climate change between human and biosphere components of the coupled model, mitigating a major source of uncertainty identified in assessments of future climate projections8-10.« less

Potential reduction in terrestrial salamander ranges associated with Marcellus shale development

USGS Publications Warehouse

Brand, Adrianne B,; Wiewel, Amber N. M.; Grant, Evan H. Campbell

2014-01-01

Natural gas production from the Marcellus shale is rapidly increasing in the northeastern United States. Most of the endemic terrestrial salamander species in the region are classified as ‘globally secure’ by the IUCN, primarily because much of their ranges include state- and federally protected lands, which have been presumed to be free from habitat loss. However, the proposed and ongoing development of the Marcellus gas resources may result in significant range restrictions for these and other terrestrial forest salamanders. To begin to address the gaps in our knowledge of the direct impacts of shale gas development, we developed occurrence models for five species of terrestrial plethodontid salamanders found largely within the Marcellus shale play. We predicted future Marcellus shale development under several scenarios. Under scenarios of 10,000, 20,000, and 50,000 new gas wells, we predict 4%, 8%, and 20% forest loss, respectively, within the play. Predictions of habitat loss vary among species, but in general, Plethodon electromorphus and Plethodonwehrlei are predicted to lose the greatest proportion of forested habitat within their ranges if future Marcellus development is based on characteristics of the shale play. If development is based on current well locations,Plethodonrichmondi is predicted to lose the greatest proportion of habitat. Models showed high uncertainty in species’ ranges and emphasize the need for distribution data collected by widespread and repeated, randomized surveys.

The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness

USGS Publications Warehouse

Tadesse, T.; Wardlow, B.; Hayes, M.; Svoboda, M.; Brown, J.

2010-01-01

The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of "historical patterns" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in the Mancha Oriental system (Spain)

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Peña-Haro, S.; García-Prats, A.; Mocholi-Almudever, A. F.; Henriquez-Dole, L.; Macian-Sorribes, H.; Lopez-Nicolas, A.

2015-04-01

Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation. Land use and land cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands, which will alter the hydrologic cycle and subsequently impact the quantity and quality of regional water systems. Predicting groundwater recharge and discharge conditions under future climate and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system (MOS), one of the largest groundwater bodies in Spain, the transformation from dry to irrigated lands during the last decades has led to a significant drop of the groundwater table, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Understanding the spatial and temporal distribution of water quantity and water quality is essential for a proper management of the system. On the one hand, streamflow depletion is compromising the dependent ecosystems and the supply to the downstream demands, provoking a complex management issue. On the other hand, the intense use of fertilizer in agriculture is leading to locally high groundwater nitrate concentrations. In this paper we analyze the potential impacts of climate and land use change in the system by using an integrated modeling framework that consists in sequentially coupling a watershed agriculturally based hydrological model (Soil and Water Assessment Tool, SWAT) with a groundwater flow model developed in MODFLOW, and with a nitrate mass-transport model in MT3DMS. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing evapotranspiration (ET) and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3DMS inputs for assessing the fate and transport of nitrate leached from the topsoil. Three climate change scenarios have been considered, corresponding to three different general circulation models (GCMs) for emission scenario A1B that covers the control period, and short-, medium- and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends (from remote-sensing images) and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections were used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. Simulated values of river discharge, crop yields, groundwater levels and nitrate concentrations fit well to the observed ones. The results show the response of groundwater quantity and quality (nitrate pollution) to climate and land use changes, with decreasing groundwater recharge and an increase in nitrate concentrations. The sequential modeling chain has been proven to be a valuable assessment tool for supporting the development of sustainable management strategies.

Extinction risks of Amazonian plant species.

PubMed

Feeley, Kenneth J; Silman, Miles R

2009-07-28

Estimates of the number, and preferably the identity, of species that will be threatened by land-use change and habitat loss are an invaluable tool for setting conservation priorities. Here, we use collections data and ecoregion maps to generate spatially explicit distributions for more than 40,000 vascular plant species from the Amazon basin (representing more than 80% of the estimated Amazonian plant diversity). Using the distribution maps, we then estimate the rates of habitat loss and associated extinction probabilities due to land-use changes as modeled under 2 disturbance scenarios. We predict that by 2050, human land-use practices will have reduced the habitat available to Amazonian plant species by approximately 12-24%, resulting in 5-9% of species becoming "committed to extinction," significantly fewer than other recent estimates. Contrary to previous studies, we find that the primary determinant of habitat loss and extinction risk is not the size of a species' range, but rather its location. The resulting extinction risk estimates are a valuable conservation tool because they indicate not only the total percentage of Amazonian plant species threatened with extinction but also the degree to which individual species and habitats will be affected by current and future land-use changes.

Forests and future water stress in the Southeast

Treesearch

Stephanie Worley Firley

2009-01-01

How will future water supplies be impacted by a changing climate, an increasing population, and shifting land uses and land cover? Will there be enough water to sustain humans and ecosystems alike? And what can be done to help forests adapt to limited water supplies in the future?

QUANTIFYING AN UNCERTAIN FUTURE: HYDROLOGIC MODEL PERFORMANCE FOR A SERIES OF REALIZED "FUTURE" CONDITIONS

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Future scenarios can be developed through a combination of modifications to the land-cover/use maps used to parameterize hydr...

Integrating landscape ecology and geoinformatics to decipher landscape dynamics for regional planning.

PubMed

Dikou, Angela; Papapanagiotou, Evangelos; Troumbis, Andreas

2011-09-01

We used remote sensing and GIS in conjunction with multivariate statistical methods to: (i) quantify landscape composition (land cover types) and configuration (patch density, diversity, fractal dimension, contagion) for five coastal watersheds of Kalloni gulf, Lesvos Island, Greece, in 1945, 1960, 1971, 1990 and 2002/2003, (ii) evaluate the relative importance of physical (slope, geologic substrate, stream order) and human (road network, population density) variables on landscape composition and configuration, and (iii) characterize processes that led to land cover changes through land cover transitions between these five successive periods in time. Distributions of land cover types did not differ among the five time periods at the five watersheds studied because the largest cumulative changes between 1945 and 2002/2003 did not take place at dominant land cover types. Landscape composition related primarily to the physical attributes of the landscape. Nevertheless, increase in population density and the road network were found to increase heterogeneity of the landscape mosaic (patchiness), complexity of patch shape (fractal dimension), and patch disaggregation (contagion). Increase in road network was also found to increase landscape diversity due to the creation of new patches. The main processes involved in land cover changes were plough-land abandonment and ecological succession. Landscape dynamics during the last 50 years corroborate the ecotouristic-agrotouristic model for regional development to reverse trends in agricultural land abandonment and human population decline and when combined with hypothetical regulatory approaches could predict how this landscape could develop in the future, thus, providing a valuable tool to regional planning.

Land use determinants of small mammal abundance and distribution in a plague endemic area of Lushoto District, Tanzania.

PubMed

Hieronimo, Proches; Kimaro, Didas N; Kihupi, Nganga I; Gulinck, Hubert; Mulungu, Loth S; Msanya, Balthazar M; Leirs, Herwig; Deckers, Jozef A

2014-07-01

Small mammals are considered to be involved in the transmission cycle of bubonic plague, still occurring in different parts of the world, including the Lushoto District in Tanzania. The objective of this study was to determine the relationship between land use types and practices and small mammal abundance and distribution. A field survey was used to collect data in three landscapes differing in plague incidences. Data collection was done both in the wet season (April-June 2012) and dry season (August-October 2012). Analysis of variance and Boosted Regression Trees (BRT) modelling technique were used to establish the relationship between land use and small mammal abundance and distribution. Significant variations (p ≤ 0.05) of small mammal abundance among land use types were identified. Plantation forest with farming, natural forest and fallow had higher populations of small mammals than the other aggregated land use types. The influence of individual land use types on small mammal abundance level showed that, in both dry and wet seasons, miraba and fallow tended to favour small mammals' habitation whereas land tillage practices had the opposite effect. In addition, during the wet season crop types such as potato and maize appeared to positively influence the distribution and abundance of small mammals which was attributed to both shelter and food availability. Based on the findings from this study it is recommended that future efforts to predict and map spatial and temporal human plague infection risk at fine scale should consider the role played by land use and associated human activities on small mammal abundance and distribution.

A National Disturbance Modeling System to Support Ecological Carbon Sequestration Assessments

NASA Astrophysics Data System (ADS)

Hawbaker, T. J.; Rollins, M. G.; Volegmann, J. E.; Shi, H.; Sohl, T. L.

2009-12-01

The U.S. Geological Survey (USGS) is prototyping a methodology to fulfill requirements of Section 712 of the Energy Independence and Security Act (EISA) of 2007. At the core of the EISA requirements is the development of a methodology to complete a two-year assessment of current carbon stocks and other greenhouse gas (GHG) fluxes, and potential increases for ecological carbon sequestration under a range of future climate changes, land-use / land-cover configurations, and policy, economic and management scenarios. Disturbances, especially fire, affect vegetation dynamics and ecosystem processes, and can also introduce substantial uncertainty and risk to the efficacy of long-term carbon sequestration strategies. Thus, the potential impacts of disturbances need to be considered under different scenarios. As part of USGS efforts to meet EISA requirements, we developed the National Disturbance Modeling System (NDMS) using a series of statistical and process-based simulation models. NDMS produces spatially-explicit forecasts of future disturbance locations and severity, and the resulting effects on vegetation dynamics. NDMS is embedded within the Forecasting Scenarios of Future Land Cover (FORE-SCE) model and informs the General Ensemble Biogeochemical Modeling System (GEMS) for quantifying carbon stocks and GHG fluxes. For fires, NDMS relies on existing disturbance histories, such as the Landsat derived Monitoring Trends in Burn Severity (MTBS) and Vegetation Change Tracker (VCT) data being used to update LANDFIRE fuels data. The MTBS and VCT data are used to parameterize models predicting the number and size of fires in relation to climate, land-use/land-cover change, and socioeconomic variables. The locations of individual fire ignitions are determined by an ignition probability surface and then FARSITE is used to simulate fire spread in response to weather, fuels, and topography. Following the fire spread simulations, a burn severity model is used to determine annual changes in biomass pools. Vegetation succession among LANDFIRE vegetation types is initiated using burn perimeter and severity data at the end of each annual simulation. Results from NDMS are used to update land-use/land-cover layers used by FORE-SCE and also transferred to GEMS for quantifying and updating carbon stocks and greenhouse gas fluxes. In this presentation, we present: 1) an overview of NDMS and its role in USGS's national ecological carbon sequestration assessment; 2) validation of NDMS using historic data; and 3) initial forecasts of disturbances for the southeastern United States and their impacts on greenhouse gas emissions, and post-fire carbon stocks and fluxes.

Baseline and Projected Future Carbon Stocks and Fluxes in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Selmants, P. C.; Sleeter, B. M.; Giardina, C. P.; Zhu, Z.; Asner, G. P.

2016-12-01

Hawaii is characterized by steep climatic gradients and heterogeneous land cover within a small geographic area, presenting a model tropical system to capture ecosystem carbon dynamics across a wide range of climate, soil, and land use conditions. However, ecosystem carbon balance is poorly understood on a statewide level, and the potential for climate and land use change to affect carbon dynamics in Hawaii has not been formally assessed. We estimated current baseline and projected future ecosystem carbon stocks and fluxes on the seven main Hawaiian Islands using a combination of remote sensing, published plot-level data, and simulation modeling. Total ecosystem carbon storage during the baseline period was estimated at 258 TgC, with 70% stored as soil organic carbon, 25% as live biomass and 5% as surface detritus, and gross primary production was estimated at 20 TgC y-1. Net ecosystem carbon balance, which incorporated carbon losses from freshwater aquatic fluxes to nearshore waters and wildland fire emissions, was estimated as 0.34 TgC y-1 during the baseline period, offsetting 7% of anthropogenic emissions. We used a state and transition simulation model to estimate the response of ecosystem carbon stocks and fluxes to potential changes in climate, land use, and wildfire over a 50-year projection period (2012-2061). Total ecosystem carbon storage was projected to increase by 5% by the year 2061, but net ecosystem carbon balance was projected to decline by 35% due to climate change induced reductions in statewide net primary production and increased carbon losses from land use and land cover change. Our analysis indicates that the State of Hawaii would remain a net carbon sink overall, primarily because of ecosystem carbon sequestration on Hawaii Island, but predicted changes in climate and land use on Kauai and Oahu would convert these islands to net carbon sources. The Hawaii carbon assessment is part of a larger effort by the U.S. Geological Survey to assess the carbon sequestration potential of ecosystems across the United States and should provide valuable information for setting research and policy priorities for sustainable carbon management strategies aimed at offsetting anthropogenic carbon emissions.

MODELING WILDLIFE HABITAT SUITABILITY IN THE WILLAMETTE BASIN: A COMPARISON OF PAST, PRESENT AND A RANGE OF POSSIBLE FUTURES (CA. 2050)

EPA Science Inventory

The effects of three possible land use futures in the Willamette Basin are evaluated with respect to present and historic conditions of wildlife habitat. Basin wide land use/land cover maps were developed by the Pacific Northwest Ecosystem Research Consortium (PNW-ERC) in coopera...

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

DOE PAGES

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.; ...

2016-08-29

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

Using Current and Historic Climate Data and Bayesian Belief Networks to Predict Optimum Satellite Image Acquisition Periods for Detecting Cheatgrass on the Snake River Plain, Idaho

NASA Astrophysics Data System (ADS)

Rope, R. C.; Ames, D. P.; Jerry, T. D.; Cherry, S. J.

2005-12-01

Invasive plant species, such as Bromus tectorum (cheatgrass), cost the United States over $36 billion per year and have encroached upon over 100 million acres while impacting range site productivity, disturbing wildlife habitat, altering the wildland fire regime and frequencies, and reducing biodiversity. Because of these adverse impacts, federal, tribal, state, and county land managers are faced with the challenge of prevention, early detection, management, and monitoring of invasive plants. Often these managers rely on the analysis of remotely sensed imagery as part of their management plan. However, it's difficult to predict specific phenological events that allow for the spectral discrimination of invasive species using only remotely sensed imagery. To address this issue tools are being developed to model and view optimal periods to collect high spatial and/or spectral resolution remotely sensed data for refined detection and mapping of invasive species and for use as a decision support tool for land managers. These tools involve the integration of historic and current climate data (cumulative growing days and precipitation) satellite imagery (MODIS) and Bayesian Belief Networks, and a web ArcIMS application to distribute the information. The general approach is to issue an initial forecast early in the year based on the previous years' data. As the year progresses, air temperature, precipitation and newly acquired low resolution MODIS satellite imagery will be used to update the prediction. Updating will be accomplished using a Bayesian Belief Network model that indicates the probabilistic relationships between prior years' conditions and those of the current year. These tools have specific application in providing a means for which land managers can efficiently and effectively detect, map, and monitor invasive plant species, specifically cheatgrass, in western rangelands. This information can then be integrated into management studies and plans to help land managers more accurately and completely determine areas infested with cheatgrass to aid in their eradication practices and future management plans.

Development of integrated scenarios to assess future conditions of aquatic ecosystems under water scarcity in the Mediterranean - perspectives from the GLOBAQUA project

NASA Astrophysics Data System (ADS)

Huber-Garcia, Verena; Akinsete, Ebun; Gampe, David; Ker Rault, Philippe; Kok, Kasper; Koundouri, Phoebe; Luttik, Joke; Nikulin, Grigory; Pistocchi, Alberto; Souliotis, Ioannis; Ludwig, Ralf

2017-04-01

Water and water-related services are major components of the human wellbeing, and as such are major factors of socio-economic development; yet freshwater systems are under threat by a variety of stressors (organic and inorganic pollution, geomorphological alterations, land cover change, water abstraction, invasive species and pathogens). Water scarcity is most commonly associated with inappropriate water management and resulting river flow reductions. It has become one of the most important drivers of change in freshwater ecosystems. Conjoint occurrence of a myriad of stressors (chemical, geomorphological, biological) under water scarcity will produce novel and unfamiliar synergies and most likely very pronounced effects. Stressors are hierarchically arranged in terms of intensity, frequency and scale, and their effects can be predicted to be from transient to irreversible. Most ecosystems are simulta¬neously exposed to multiple-stress situations. Within the scope of the GLOBAQUA project the effects of multiple stressors on aquatic ecosystems in selected river basins across Europe with a focus on areas suffering from water scarcity are analyzed. In addition, management strategies are improved and adapted with the aim of inhibiting adverse effects on aquatic ecosystems and ensuring the supply with water for all purposes in the study areas also in the future. Policy relevant implications will be given to ensure a best possible status of these aquatic ecosystems also under future conditions. In this context, land use and land cover as well as the meteorological conditions can be seen as two main stressors for the quality and quantity of surface and subsurface water. These factors considerably affect the use and availability of water, especially in regions which already experience water scarcity. If the problem is not addressed correctly, negative effects on biodiversity, water supply as well as important economic consequences may arise. In Europe, many fresh water systems experience this and a worsening of the situation can be expected if actions are not taken. To assess future conditions, spatially distributed, integrated scenarios to drive various impact models are inevitable. These simulations then assess future conditions of aquatic ecosystems, both in water quality and quantity, and in the end provide decision support. To achieve this goal, a modeling framework is set up to develop integrated scenarios of changes in climate, land use and water management. These scenarios are based on storylines around various Representative Concentration Pathways (RCPs) and Shared Socio-economic Pathways (SSPs), as established the Intergovernmental Panel on Climate Change (IPCC), and developed in collaboration with project partners and experts. Major challenges stem from the downscaling of these to the regional scale. Projections of future climate conditions originate from the simulations provided through the EURO-CORDEX project. An ensemble of different General Circulation Models (GCMs) driving various Regional Climate Models (RCMs) is available. After a thorough investigation of these projections and an estimation of the uncertainty envelope, a small subset of models was chosen in a carefully conducted selection procedure, following a cluster analysis. These selected simulations were downscaled to better represent the regional conditions and provide the implications of the RCPs in the storylines. The impacts of the SSPs are represented in spatially distributed land use maps developed through the land use change model iCLUE (Conversion of Land Use and its Effects). In a first step knowledge on past land use change is required and an analysis was carried out based on the CORINE land cover data. Extensive expert surveys have been conducted in the case study areas to determine the most important drivers of these changes, considering both, biophysical and socio-economic variables. The results of these were implemented in iCLUE taking into account dynamic changes of the climate, population and economy. Climate and land use projections will then be applied to provide possible future conditions and various impact modeling activities within the GLOBAQUA project. This approach is favored over a non-integrated approach using only climate projections, and required to develop and test site specific Programs of Measures (PoMs). Eventually, decision support can be provided to local authorities for effective PoMs. [The funding for this research through the FP7-project GLOBAQUA by the European Commission (GA: 603629) is gratefully acknowledged.

Interdependencies and Risks at the Nexus of Energy, Water, and Land Systems

NASA Astrophysics Data System (ADS)

Geernaert, G. L.

2016-12-01

During recent years, the federal agencies have rallied around efforts to understand and predict the interdependencies involving various combinations of energy infrastructure and supply, water supply and quality, and land use that combines agriculture and food production. The US Department of Energy has, in particular, focused on the energy-water nexus, with specific goals to understand the degree of interdependence that leads to multi-sector risk and, in the worst case, the precursors that can lead to cascading failure. Determining thresholds for system interdependence, evaluating the impact of drought on systems, and planning for robust mitigation options to avert future risks, are among DOE's highest research priorities. In this presentation, the DOE program plan and its rationale will be described; and the DOE plan will be placed in context of broader efforts across the federal government.

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Can conservation funding be left to carbon finance? Evidence from participatory future land use scenarios in Peru, Indonesia, Tanzania, and Mexico

NASA Astrophysics Data System (ADS)

Ravikumar, Ashwin; Larjavaara, Markku; Larson, Anne; Kanninen, Markku

2017-01-01

Revenues derived from carbon have been seen as an important tool for supporting forest conservation over the past decade. At the same time, there is high uncertainty about how much revenue can reasonably be expected from land use emissions reductions initiatives. Despite this uncertainty, REDD+ projects and conservation initiatives that aim to take advantage of available or, more commonly, future funding from carbon markets have proliferated. This study used participatory multi-stakeholder workshops to develop divergent future scenarios of land use in eight landscapes in four countries around the world: Peru, Indonesia, Tanzania, and Mexico. The results of these future scenario building exercises were analyzed using a new tool, CarboScen, for calculating the landscape carbon storage implications of different future land use scenarios. The findings suggest that potential revenues from carbon storage or emissions reductions are significant in some landscapes (most notably the peat forests of Indonesia), and much less significant in others (such as the low-carbon forests of Zanzibar and the interior of Tanzania). The findings call into question the practicality of many conservation programs that hinge on expectations of future revenue from carbon finance. The future scenarios-based approach is useful to policy-makers and conservation program developers in distinguishing between landscapes where carbon finance can substantially support conservation, and landscapes where other strategies for conservation and land use should be prioritized.

'Underutilised' agricultural land: its definitions, potential use for future biomass production and its environmental implications

NASA Astrophysics Data System (ADS)

Miyake, Saori; Bargiel, Damian

2017-04-01

A growing bioeconomy and increased demand for biomass products on food, health, fibre, industrial products and energy require land resources for feedstock production. It has resulted in significant environmental and socio-economic challenges on a global scale. As a result, consideration of such effects of land use change (LUC) from biomass production (particularly for biofuel feedstock) has emerged as an important area of policy and research, and several potential solutions have been proposed to minimise such adverse LUC effects. One of these solutions is the use of lands that are not in production or not suitable for food crop production, such as 'marginal', 'degraded', 'abandoned' and 'surplus' agricultural lands for future biomass production. The terms referring to these lands are usually associated with the potential production of 'marginal crops', which can grow in marginal conditions (e.g. poor soil fertility, low rainfall, drought) without much water and agrochemical inputs. In our research, we referred to these lands as 'underutilised' agricultural land and attempted to define them for our case study areas located in Australia and Central and Eastern Europe (CEE). Our goal is to identify lands that can be used for future biomass production and to evaluate their environmental implications, particularly impacts related to biodiversity, water and soil at a landscape scale. The identification of these lands incorporates remote sensing and spatially explicit approaches. Our findings confirmed that there was no universal or single definition of the term 'underutilised' agricultural land as the definitions significantly vary by country and region depending not only on the biophysical environment but also political, institutional and socio-economic conditions. Moreover, our results highlighted that the environmental implications of production of biomass on 'underutilised' agricultural land for biomass production are highly controversial. Thus land use change scenarios with low-impact crops and production system must be designed for future biomass production taking into consideration climate, land use, local biophysical conditions and relevant policies (e.g. conservation) within a regional/ landscape planning framework.

Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment.

PubMed

Wagner, Paul D; Bhallamudi, S Murty; Narasimhan, Balaji; Kantakumar, Lakshmi N; Sudheer, K P; Kumar, Shamita; Schneider, Karl; Fiener, Peter

2016-01-01

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance. Copyright © 2015 Elsevier B.V. All rights reserved.

Interactions Between Land Use, Climate and Hydropower in Scotland

NASA Astrophysics Data System (ADS)

Sample, J.

2014-12-01

To promote the transition towards a low carbon economy, the Scottish Government has adopted ambitious energy targets, including generating all electricity from renewable sources by 2020. To achieve this, continued investment will be required across a range of sustainable technologies. Hydropower has a long history in Scotland and the present-day operational capacity of ~1.5 GW makes a substantial contribution to the national energy budget. In addition, there remains potential for ~500 MW of further development, mostly in the form of small to medium size run-of-river schemes. Climate change is expected to lead to an intensification of the global hydrological cycle, leading to changes in both the magnitude and seasonality of river flows. There may also be indirect effects, such as changing land use, enhanced evapotranspiration rates and an increased demand for irrigation, all of which could affect the water available for energy generation. Preliminary assessments of hydropower commonly use flow duration curves (FDCs) to estimate the power generation potential at proposed new sites. In this study, we use spatially distributed modelling to generate daily and monthly FDCs for a range of Scottish catchments using a variety of future land use and climate change scenarios. These are then used to assess Scotland's future hydropower potential under different flow regimes. The results are spatially variable and include large uncertainties, but some consistent patterns emerge. Many locations are predicted to experience enhanced seasonality, with lower power generation potential in the summer months and greater potential during the autumn and winter. Some sites may require infrastructural changes in order to continue operating at optimum efficiency. We discuss the implications and limitations of our results, and highlight design and adaptation options for maximising the resilience of hydropower installations under changing future flow patterns.

Fluvial Sediments as GeoArchives in the Tsauchab Valley, Namibia

NASA Astrophysics Data System (ADS)

Völkel, Jörg; Bens, Oliver; Eden, Marie; Heine, Klaus; Hürkamp, Kerstin

2015-04-01

Understanding the history of how humans have interacted with the landscape can help clarify the options for managing our increasingly interconnected global system. In consequence of changing climate, major regional impacts on the human habitat is expected and must be addressed in modern land-use planning and management strategies which in turn has to rely on a diligent assessment of the nature of possible impacts on regional environments. In warm arid and semi-arid climatic zones, land use can result in landscape degradation, leading to enhanced activity of earth surface processes. Climatic changes can also be instrumental in producing landscape and ecosystem changes, similar to earth surface processes brought about by land-use change. However, predictions of the future behaviour of complex geo/bio-systems are limited, because these are open systems. Apart from modelling a promising approach to better understand the processes of environment responses is to learn lessons from past variability, i.e. searching for 'palaeo-analogue' situations. These are time intervals in the past with boundary conditions (e.g. sea-level changes, atmospheric circulation patterns) more similar to future scenarios than to the present day situation. Signals of these past climate and ecosystem changes are stored in a variety of natural continental and marine archives (sediments, biogens). These geoarchives have the potential for providing researchers with high-resolution data for the reconstruction of palaeo-ecosystems and their dynamics. The influence of key forcing variables and their effects extracted from the geoarchives will be cross-checked in order to validate and adjust models of present and future processes. This knowledge will help justify and calibrate prognostic scenarios in order to deliver proxy-data for southern-hemisphere records. - The project "GeoArchives" is funded by BMBF within the SPACES-Program.

Climate mitigation and the future of tropical landscapes.

PubMed

Thomson, Allison M; Calvin, Katherine V; Chini, Louise P; Hurtt, George; Edmonds, James A; Bond-Lamberty, Ben; Frolking, Steve; Wise, Marshall A; Janetos, Anthony C

2010-11-16

Land-use change to meet 21st-century demands for food, fuel, and fiber will depend on many interactive factors, including global policies limiting anthropogenic climate change and realized improvements in agricultural productivity. Climate-change mitigation policies will alter the decision-making environment for land management, and changes in agricultural productivity will influence cultivated land expansion. We explore to what extent future increases in agricultural productivity might offset conversion of tropical forest lands to crop lands under a climate mitigation policy and a contrasting no-policy scenario in a global integrated assessment model. The Global Change Assessment Model is applied here to simulate a mitigation policy that stabilizes radiative forcing at 4.5 W m(-2) (approximately 526 ppm CO(2)) in the year 2100 by introducing a price for all greenhouse gas emissions, including those from land use. These scenarios are simulated with several cases of future agricultural productivity growth rates and the results downscaled to produce gridded maps of potential land-use change. We find that tropical forests are preserved near their present-day extent, and bioenergy crops emerge as an effective mitigation option, only in cases in which a climate mitigation policy that includes an economic price for land-use emissions is in place, and in which agricultural productivity growth continues throughout the century. We find that idealized land-use emissions price assumptions are most effective at limiting deforestation, even when cropland area must increase to meet future food demand. These findings emphasize the importance of accounting for feedbacks from land-use change emissions in global climate change mitigation strategies.

Future methane emissions from animals

NASA Astrophysics Data System (ADS)

Anastasi, C.; Simpson, V. J.

1993-04-01

The future global emission of CH4 from enteric fermentation in animals has been estimated for cattle, sheep, and buffalo, which together contribute approximately 91% of the total CH4 emitted from domesticated animals at present. A simple model has been used to relate livestock levels to the national human populations for each country involved in breeding the three species included in this analysis. United Nations population predictions to 2025 were then included in the model to estimate future CH4 emissions. A variational analysis was carried out to investigate the effect of future changes in both the land available for grazing and the nutritional content of feedstocks. Results suggest that the total emission of CH4 from enteric fermentation in domestic animals will increase from 84 Tg CH4 per year (Tg = 1012 g) in 1990 to 119 (±12) Tg CH4 yr-1 by 2025. These values correspond to an average rate of increase over the next 35 years of 1.0 Tg CH4 yr-1.

Climate and human intervention effects on future fire activity and consequences for air pollution across the 21st century

NASA Astrophysics Data System (ADS)

Val Martin, M.; Pierce, J. R.; Heald, C. L.; Li, F.; Lawrence, D. M.; Wiedinmyer, C.; Tilmes, S.; Vitt, F.

2016-12-01

Emissions of aerosols and gases from fires have been shown to adversely affect air quality across the world. Fire activity is strongly related to climate and anthropogenic activities. Current fire projections for the 21st century seem very uncertain, ranging from increasing to declining depending on the climate, land cover change and population growth scenarios used. Here we present an analysis of the changes in future wildfire activity and consequences on air quality, with focus on PM2.5 and surface O3 over regions vulnerable to fire. We use the global Community Earth System Model (CESM) with a process-based fire model to simulate emissions from agriculture, peatland, deforestation and landscape fires for present-day and throughout the current century. We consider two future Representative Concentration Pathways climate scenarios combined with population density changes predicted from Shared Socio-economic Pathways to project climate and demographic effects on fire activity and further consequences for future air quality.

Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon.

PubMed

Galford, Gillian L; Melillo, Jerry M; Kicklighter, David W; Cronin, Timothy W; Cerri, Carlos E P; Mustard, John F; Cerri, Carlos C

2010-11-16

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed

NASA Astrophysics Data System (ADS)

Jyrkama, M. I.; Sykes, J. F.

2004-05-01

The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

PubMed Central

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses. PMID:27348224

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

PubMed

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995-2014) and near future (2015-2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

In ecoregions across western USA streamflow increases during post-wildfire recovery

NASA Astrophysics Data System (ADS)

Wine, Michael L.; Cadol, Daniel; Makhnin, Oleg

2018-01-01

Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%-14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%-370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

The variability of runoff and soil erosion in the Brazilian Cerrado biome due to the potential land use and climate changes

NASA Astrophysics Data System (ADS)

Alexandre Ayach Anache, Jamil; Wendland, Edson; Malacarne Pinheiro Rosalem, Lívia; Srivastava, Anurag; Flanagan, Dennis

2017-04-01

Changes in land use and climate can influence runoff and soil loss, threatening soil and water conservation in the Cerrado biome in Brazil. Due to the lack of long term observed data for runoff and soil erosion in Brazil, the adoption of a process-based model was necessary, representing the variability of both variables in a continuous simulation approach. Thus, we aimed to calibrate WEPP (Water Erosion Prediction Project) model for different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane) under subtropical conditions inside the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change scenarios. We performed the model calibration using a 4-year dataset of observed runoff and soil loss in four different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane). The WEPP model components (climate, topography, soil, and management) were calibrated according to field data. However, soil and management were optimized according to each land use using a parameter estimation tool. The observations were conducted between 2012 and 2015 in experimental plots (5 m width, 20 m length, 9% slope gradient, 3 replicates per treatment). The simulations were done using the calibrated WEPP model components, but changing the 4-year observed climate file by a 100-year dataset created with CLIGEN (weather generator) based on regional climate statistics. Afterwards, using MarkSim DSSAT Weather File Generator, runoff and soil loss were simulated using future climate scenarios for 2030, 2060, and 2090. To analyze the data, we used non-parametric statistics as data do not follow normal distribution. The results show that WEPP model had an acceptable performance for the considered conditions. In addition, both land use and climate can influence on runoff and soil loss rates. Potential climate changes which consider the increase of rainfall intensities and depths in the studied region may increase the variability and rates for runoff and soil erosion. However, the climate did not change the differences and similarities between the rates of the four analyzed land uses. The runoff behavior is distinct for all land uses, but for soil loss we found similarities between pasture and undisturbed Cerrado, suggesting that soil sustainability could be reached when the management follows conservation principles.

Land-use and land-cover scenarios and spatial modeling at the regional scale

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.

2012-01-01

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

Evaluating the Connectivity of a Protected Areas' Network under the Prism of Global Change: The Efficiency of the European Natura 2000 Network for Four Birds of Prey

PubMed Central

Mazaris, Antonios D.; Papanikolaou, Alexandra D.; Barbet-Massin, Morgane; Kallimanis, Athanasios S.; Jiguet, Frédéric; Schmeller, Dirk S.; Pantis, John D.

2013-01-01

Climate and land use changes are major threats to biodiversity. To preserve biodiversity, networks of protected areas have been established worldwide, like the Natura 2000 network across the European Union (EU). Currently, this reserve network consists of more than 26000 sites covering more than 17% of EU terrestrial territory. Its efficiency to mitigate the detrimental effects of land use and climate change remains an open research question. Here, we examined the potential current and future geographical ranges of four birds of prey under scenarios of both land use and climate changes. By using graph theory, we examined how the current Natura 2000 network will perform in regard to the conservation of these species. This approach determines the importance of a site in regard to the total network and its connectivity. We found that sites becoming unsuitable due to climate change are not a random sample of the network, but are less connected and contribute less to the overall connectivity than the average site and thus their loss does not disrupt the full network. Hence, the connectivity of the remaining network changed only slightly from present day conditions. Our findings highlight the need to establish species-specific management plans with flexible conservation strategies ensuring protection under potential future range expansions. Aquila pomarina is predicted to disappear from the southern part of its range and to become restricted to northeastern Europe. Gyps fulvus, Aquila chrysaetos, and Neophron percnopterus are predicted to locally lose some suitable sites; hence, some isolated small populations may become extinct. However, their geographical range and metapopulation structure will remain relatively unaffected throughout Europe. These species would benefit more from an improved habitat quality and management of the existing network of protected areas than from increased connectivity or assisted migration. PMID:23527237

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

NASA Astrophysics Data System (ADS)

Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan

2017-12-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.

Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Stamm, Christian

2017-03-01

The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

Development of advanced entry, descent, and landing technologies for future Mars Missions

NASA Technical Reports Server (NTRS)

Chu, Cheng-Chih (Chester)

2006-01-01

Future Mars missions may need the capability to land much closer to a desired target and/or advanced methods of detecting, avoiding, or tolerating landing hazards. Therefore, technologies that enable 'pinpoint landing' (within tens of meters to 1 km of a target site) will be crucial to meet future mission requirements. As part of NASA Research Announcement, NRA 03-OSS-01, NASA solicited proposals for technology development needs of missions to be launched to Mars during or after the 2009 launch opportunity. Six technology areas were identified as of high priority including advanced entry, descent, and landing (EDL) technologies. In May 2004, 11 proposals with PIs from universities, industries, and NASA centers, were awarded in the area of advanced EDL by NASA for further study and development. This paper presents an overview of these developing technologies.

Land-use threats and protected areas: a scenario-based, landscape level approach

USGS Publications Warehouse

Wilson, Tamara S.; Sleeter, Benjamin M.; Sleeter, Rachel R.; Soulard, Christopher E.

2014-01-01

Anthropogenic land use will likely present a greater challenge to biodiversity than climate change this century in the Pacific Northwest, USA. Even if species are equipped with the adaptive capacity to migrate in the face of a changing climate, they will likely encounter a human-dominated landscape as a major dispersal obstacle. Our goal was to identify, at the ecoregion-level, protected areas in close proximity to lands with a higher likelihood of future land-use conversion. Using a state-and-transition simulation model, we modeled spatially explicit (1 km2) land use from 2000 to 2100 under seven alternative land-use and emission scenarios for ecoregions in the Pacific Northwest. We analyzed scenario-based land-use conversion threats from logging, agriculture, and development near existing protected areas. A conversion threat index (CTI) was created to identify ecoregions with highest projected land-use conversion potential within closest proximity to existing protected areas. Our analysis indicated nearly 22% of land area in the Coast Range, over 16% of land area in the Puget Lowland, and nearly 11% of the Cascades had very high CTI values. Broader regional-scale land-use change is projected to impact nearly 40% of the Coast Range, 30% of the Puget Lowland, and 24% of the Cascades (i.e., two highest CTI classes). A landscape level, scenario-based approach to modeling future land use helps identify ecoregions with existing protected areas at greater risk from regional land-use threats and can help prioritize future conservation efforts.

The Land Use Model Intercomparison Project (LUMIP) Contribution to CMIP6: Rationale and Experimental Design

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Hurtt, G. C.; Arneth, A.; Brovkin, V.; Calvin, K. V.; Jones, A. D.; Jones, C.; Lawrence, P.; De Noblet-Ducoudré, N.; Pongratz, J.; Seneviratne, S. I.; Shevliakova, E.

2016-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and (3) Are there regional land-management strategies with promise to help mitigate against climate change? LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. Foci will include separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that CO2 fertilization is modulated by past and future land use. LUMIP involves three sets of activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for LUMIP experiments, and (3) definition of metrics that quantify model performance with respect to LULCC. LUMIP experiments are designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate. LUMIP also includes simulations that allow quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. We will present the experimental protocol in detail, explain the rationale, outlines plans for analysis, and describe a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types).

Monitoring and predicting eutrophication of Sri Lankan inland waters using ASTER satellite data

NASA Astrophysics Data System (ADS)

Dahanayaka, D. D. G. L.; Wijeyaratne, M. J. S.; Tonooka, H.; Minato, A.; Ozawa, S.; Perera, B. D. C.

2014-10-01

This study focused on determining the past changes and predicting the future trends in eutrophication of the Bolgoda North lake, Sri Lanka using in situ Chlorophyll-a (Chl-a) measurements and Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) satellite data. This Lake is located in a mixed land use area with industries, some agricultural lands, middle income and high income housing, tourist hotels and low income housing. From March to October 2013, water samples from five sampling sites were collected once a month parallel to ASTER overpass and Chl-a, nitrate and phosphate contents of each sample were measured using standard laboratory methods. Cloud-free ASTER scenes over the lake during the 2000-2013 periods were acquired for Chl-a estimation and trend analysis. All ASTER images were atmospherically corrected using FLAASH software and in-situ Chl-a data were regressed with atmospherically corrected three ASTER VNIR band ratios of the same date. The regression equation of the band ratio and Chl-a content with the highest correlation, which was the green/red band ratio was used to develop algorithm for generation of 15-m resolution Chl-a distribution maps. According to the ASTER based Chl-a distribution maps it was evident that eutrophication of this lake has gradually increased from 2008-2011. Results also indicated that there had been significantly high eutrophic conditions throughout the year 2013 in several regions, especially in water stagnant areas and adjacent to freshwater outlets. Field observations showed that this lake is receiving various discharges from factories. Unplanned urbanization and inadequacy of proper facilities in the nearby industries for waste management have resulted in the eutrophication of the water body. If the present trends of waste disposal and unplanned urbanization continue, enormous environmental problems would be resulted in future. Results of the present study showed that information from satellite remote sensing can play a useful role in the development of time series Chl-a distribution maps. Such information is important for the future predictions, development and management of this area as well as in the conservation of this water body.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

NASA Astrophysics Data System (ADS)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena

2016-09-01

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE PAGES

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; ...

2016-09-02

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

NASA Astrophysics Data System (ADS)

Suzuki, Kazuyoshi; Zupanski, Milija

2018-01-01

In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

Collaborative development of land use change scenarios for analysing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

Malek, Žiga; Glade, Thomas

2015-04-01

Simulating future land use changes remains a difficult task, due to uncontrollable and uncertain driving forces of change. Scenario development emerged as a tool to address these limitations. Scenarios offer the exploration of possible futures and environmental consequences, and enable the analysis of possible decisions. Therefore, there is increasing interest of both decision makers and researchers to apply scenarios when studying future land use changes and their consequences. The uncertainties related to generating land use change scenarios are among others defined by the accuracy of data, identification and quantification of driving forces, and the relation between expected future changes and the corresponding spatial pattern. To address the issue of data and intangible driving forces, several studies have applied collaborative, participatory techniques when developing future scenarios. The involvement of stakeholders can lead to incorporating a broader spectrum of professional values and experience. Moreover, stakeholders can help to provide missing data, improve detail, uncover mistakes, and offer alternatives. Thus, collaborative scenarios can be considered as more reliable and relevant. Collaborative scenario development has been applied to study a variety of issues in environmental sciences on different spatial and temporal scales. Still, these participatory approaches are rarely spatially explicit, making them difficult to apply when analysing changes to hydro-meteorological risk on a local scale. Spatial explicitness is needed to identify potentially critical areas of land use change, leading to locations where the risk might increase. In order to allocate collaboratively developed scenarios of land change, we combined participatory modeling with geosimulation in a multi-step scenario generation framework. We propose a framework able to develop scenarios that are plausible, can overcome data inaccessibility, address intangible and external driving forces of land change, and is transferable to other case study areas with different land use change processes and consequences. The framework starts with the involvement of stakeholders where driving forces of land use change are being studied by performing interviews and group discussions. In order to bridge the gap between qualitative methods and conventional geospatial techniques, we applied cognitive mapping and the Drivers-Pressures-State-Impact and Response framework (DPSIR) to develop a conceptual land use change model. This was later transformed into a spatially explicit land use change model based on remote sensing data, GIS and cellular automata spatial allocation. The methodology was developed and applied in a study area in the eastern Italian Alps, where the uncertainties regarding future urban expansion are high. Later, we transferred it to a study area in the Romanian Carpathians, where the identified prevailing process of land use change is deforestation. Both areas are subject to hydro-meteorological risk, posing a need for the analysis of the possible future spatial pattern and locations of land use change. The resulting scenarios enabled us, to point at identifying hot-spots of land use change, serving as a possible input for a risk assessment.

Potential strong contribution of future anthropogenic land-use and land-cover change to the terrestrial carbon cycle

NASA Astrophysics Data System (ADS)

Quesada, Benjamin; Arneth, Almut; Robertson, Eddy; de Noblet-Ducoudré, Nathalie

2018-06-01

Anthropogenic land-use and land cover changes (LULCC) affect global climate and global terrestrial carbon (C) cycle. However, relatively few studies have quantified the impacts of future LULCC on terrestrial carbon cycle. Here, using Earth system model simulations performed with and without future LULCC, under the RCP8.5 scenario, we find that in response to future LULCC, the carbon cycle is substantially weakened: browning, lower ecosystem C stocks, higher C loss by disturbances and higher C turnover rates are simulated. Projected global greening and land C storage are dampened, in all models, by 22% and 24% on average and projected C loss by disturbances enhanced by ~49% when LULCC are taken into account. By contrast, global net primary productivity is found to be only slightly affected by LULCC (robust +4% relative enhancement compared to all forcings, on average). LULCC is projected to be a predominant driver of future C changes in regions like South America and the southern part of Africa. LULCC even cause some regional reversals of projected increased C sinks and greening, particularly at the edges of the Amazon and African rainforests. Finally, in most carbon cycle responses, direct removal of C dominates over the indirect CO2 fertilization due to LULCC. In consequence, projections of land C sequestration potential and Earth’s greening could be substantially overestimated just because of not fully accounting for LULCC.

Threats and opportunities for freshwater conservation under future land use change scenarios in the United States.

PubMed

Martinuzzi, Sebastián; Januchowski-Hartley, Stephanie R; Pracheil, Brenda M; McIntyre, Peter B; Plantinga, Andrew J; Lewis, David J; Radeloff, Volker C

2014-01-01

Freshwater ecosystems provide vital resources for humans and support high levels of biodiversity, yet are severely threatened throughout the world. The expansion of human land uses, such as urban and crop cover, typically degrades water quality and reduces freshwater biodiversity, thereby jeopardizing both biodiversity and ecosystem services. Identifying and mitigating future threats to freshwater ecosystems requires forecasting where land use changes are most likely. Our goal was to evaluate the potential consequences of future land use on freshwater ecosystems in the coterminous United States by comparing alternative scenarios of land use change (2001-2051) with current patterns of freshwater biodiversity and water quality risk. Using an econometric model, each of our land use scenarios projected greater changes in watersheds of the eastern half of the country, where freshwater ecosystems already experience higher stress from human activities. Future urban expansion emerged as a major threat in regions with high freshwater biodiversity (e.g., the Southeast) or severe water quality problems (e.g., the Midwest). Our scenarios reflecting environmentally oriented policies had some positive effects. Subsidizing afforestation for carbon sequestration reduced crop cover and increased natural vegetation in areas that are currently stressed by low water quality, while discouraging urban sprawl diminished urban expansion in areas of high biodiversity. On the other hand, we found that increases in crop commodity prices could lead to increased agricultural threats in areas of high freshwater biodiversity. Our analyses illustrate the potential for policy changes and market factors to influence future land use trends in certain regions of the country, with important consequences for freshwater ecosystems. Successful conservation of aquatic biodiversity and ecosystem services in the United States into the future will require attending to the potential threats and opportunities arising from policies and market changes affecting land use. © 2013 John Wiley & Sons Ltd.

Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models

NASA Astrophysics Data System (ADS)

Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M.

2011-03-01

Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models.

Spatial and temporal predictions of agricultural land prices using DSM techniques.

NASA Astrophysics Data System (ADS)

Carré, F.; Grandgirard, D.; Diafas, I.; Reuter, H. I.; Julien, V.; Lemercier, B.

2009-04-01

Agricultural land prices highly impacts land accessibility to farmers and by consequence the evolution of agricultural landscapes (crop changes, land conversion to urban infrastructures…) which can turn to irreversible soil degradation. The economic value of agricultural land has been studied spatially, in every one of the 374 French Agricultural Counties, and temporally- from 1995 to 2007, by using data of the SAFER Institute. To this aim, agricultural land price was considered as a digital soil property. The spatial and temporal predictions were done using Digital Soil Mapping techniques combined with tools mainly used for studying temporal financial behaviors. For making both predictions, a first classification of the Agricultural Counties was done for the 1995-2006 periods (2007 was excluded and served as the date of prediction) using a fuzzy k-means clustering. The Agricultural Counties were then aggregated according to land price at the different times. The clustering allows for characterizing the counties by their memberships to each class centroid. The memberships were used for the spatial prediction, whereas the centroids were used for the temporal prediction. For the spatial prediction, from the 374 Agricultural counties, three fourths were used for modeling and one fourth for validating. Random sampling was done by class to ensure that all classes are represented by at least one county in the modeling and validation datasets. The prediction was done for each class by testing the relationships between the memberships and the following factors: (i) soil variable (organic matter from the French BDAT database), (ii) soil covariates (land use classes from CORINE LANDCOVER, bioclimatic zones from the WorldClim Database, landform attributes and landform classes from the SRTM, major roads and hydrographic densities from EUROSTAT, average field sizes estimated by automatic classification of remote sensed images) and (iii) socio-economic factors (population density, gross domestic product and its combination with the population density obtained from EUROSTAT). Linear (Generalized Linear Models) and non-linear models (neural network) were used for building the relationships. For the validation, the relationships were applied to the validation datasets. The RMSE and the coefficient of determination (from a linear regression) between predicted and actual memberships, and the contingency table between the predicted and actual allocation classes were used as validation criteria. The temporal prediction was done on the year 2007 from the centroid land prices characterizing the 1995-2006 period. For each class, the land prices of the time-series 1995-2006 were modeled using an Auto-Regressive Moving Average approach. For the validation, the models were applied to the year 2007. The RMSE between predicted and actual prices is used as the validation criteria. We then discussed the methods and the results of the spatial and temporal validation. Based on this methodology, an extrapolation will be tested on another European country with land price market similar to France (to be determined).

The influence of coarse-scale environmental features on current and predicted future distributions of narrow-range endemic crayfish populations

USGS Publications Warehouse

Dyer, Joseph J.; Brewer, Shannon K.; Worthington, Thomas A.; Bergey, Elizabeth A.

2013-01-01

1.A major limitation to effective management of narrow-range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2.Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate-change scenarios. 3.The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 6587% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4.Current models created using two spatial resolutions (1 and 4.5km2) showed that fine-resolution data more accurately represented current distributions. For three of the four species, the 1-km2 resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1-km2 resolution models were more accurate than 4.5-km2 resolution models. 5.Future projected (4.5-km2 resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low-emission scenario, whereas two of four species would be severely restricted in range under moderatehigh emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species-distribution models. 6.These model predictions illustrate possible impacts of climate change on narrow-range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.

A Method for Mapping Future Urbanization in the United States

NASA Technical Reports Server (NTRS)

Bounoua, Lahouari; Nigro, Joseph; Thome, Kurtis; Zhang, Ping; Fathi, Najlaa; Lachir, Asia

2018-01-01

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Evidence of Urban Precipitation Anomalies from Satellite and Ground-Based Measurements

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Manyin, M.; Negri, Andrew

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

Evidence of Urban Precipitation Anomalies from Satellite and Ground-Based Measurements

NASA Technical Reports Server (NTRS)

Shepherd, J. M.; Manyin, M.; Negri, A.

2004-01-01

Urbanization is one of the extreme cases of land use change. Most of world s population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025,60% of the world s population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause- effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

Development of a prototype land use model for statewide transportation planning activities.

DOT National Transportation Integrated Search

2011-11-30

Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

How well do we succeed in modeling the global soil carbon pools?

NASA Astrophysics Data System (ADS)

Viskari, T.; Liski, J.

2017-12-01

Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.

Optimality Based Dynamic Plant Allocation Model: Predicting Acclimation Response to Climate Change

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Drewry, D.; Kumar, P.; Sivapalan, M.

2009-12-01

Allocation of assimilated carbon to different plant parts determines the future plant status and is important to predict long term (months to years) vegetated land surface fluxes. Plants have the ability to modify their allometry and exhibit plasticity by varying the relative proportions of the structural biomass contained in each of its tissue. The ability of plants to be plastic provides them with the potential to acclimate to changing environmental conditions in order to enhance their probability of survival. Allometry based allocation models and other empirical allocation models do not account for plant plasticity cause by acclimation due to environmental changes. In the absence of a detailed understanding of the various biophysical processes involved in plant growth and development an optimality approach is adopted here to predict carbon allocation in plants. Existing optimality based models of plant growth are either static or involve considerable empiricism. In this work, we adopt an optimality based approach (coupled with limitations on plant plasticity) to predict the dynamic allocation of assimilated carbon to different plant parts. We explore the applicability of this approach using several optimization variables such as net primary productivity, net transpiration, realized growth rate, total end of growing season reproductive biomass etc. We use this approach to predict the dynamic nature of plant acclimation in its allocation of carbon to different plant parts under current and future climate scenarios. This approach is designed as a growth sub-model in the multi-layer canopy plant model (MLCPM) and is used to obtain land surface fluxes and plant properties over the growing season. The framework of this model is such that it retains the generality and can be applied to different types of ecosystems. We test this approach using the data from free air carbon dioxide enrichment (FACE) experiments using soybean crop at the Soy-FACE research site. Our results show that there are significant changes in the allocation patterns of vegetation when subjected to elevated CO2 indicating that our model is able to account for plant plasticity arising from acclimation. Soybeans when grown under elevated CO2, increased their allocation to structural components such as leaves and decreased their allocation to reproductive biomass. This demonstrates that plant acclimation causes lower than expected crop yields when grown under elevated CO2. Our findings can have serious implications in estimating future crop yields under climate change scenarios where it is widely expected that rising CO2 will fully offset losses due to climate change.

Prediction of diffuse organic micropollutant loads in streams under changing climatic, socio-economic and technical boundary conditions with an integrated transport model

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Ghielmetti, Nico; Stamm, Christian

2014-05-01

Catchments are complex systems where water quantity, quality and the ecological services provided are determined by interacting physical, chemical, biological, economical and social factors. The realization of these interactions led to the prevailing catchment management paradigm: Integrated Water Resources Management (IWRM). IWRM requires considering all these aspects during the design of sustainable resource utilization. Due to the complexity of this task, mathematical modeling plays a key role in IWRM, namely in the evaluation of the impacts of hypothetical scenarios and management measures. Toxicity is a key determinant of the ecological state and as such a focal point in IWRM, but we still have significant knowledge gaps about the diffuse loads of organic micropollutants (OMP) that leak from both urban and agricultural areas. Most European catchments possess mixed land use, containing rural (natural and agricultural) landscapes and settlements in varying proportions. Thus, a catchment model supporting IWRM must be able to cope with both classes. However, the majority of existing catchment models is dedicated to either rural or urban areas, while the minority capable of simulating both contain overly simplified descriptions for either land use category. We applied a conceptual model that describes all major land use classes for assessing the impacts of climate change, socio-economic development and management alternatives on diffuse OMP loads. We simulated the loads of 12 compounds (agricultural and urban pesticides and urban biocides) with daily resolution at 11 locations in the stream network of a small catchment (46 km2) in Switzerland. The model considers all important diffuse transport pathways separately, but each with a simple empirical process rate. Consequently, some site-specific observations were required to calibrate rate parameters. We assessed uncertainty during both calibration and prediction phases. Predictions indicated that future OMP loads were predominantly determined by human activities in each simulated sub-catchment, as reflected by the socio-economic scenarios and management alternatives. Climatic and the corresponding hydrological changes had a much weaker influence. This indicates that - conditionally on the confidence of our predictions - catchment management would possess effective options to prevent the degradation of water quality in the future. However, prediction uncertainty varied between high and huge levels depending on compound. Most of the identified uncertainty was related to the quality of input data. Application rates and timings could be estimated only roughly for most compounds. Concentration peaks were simulated with high uncertainty. The highest pollutant concentrations were often associated with known but unidentified pollution sources such as accidental spills, or brief high-intensity precipitation events whose amount could only be observed with high uncertainty. So while acute exposure would be as important as the chronic one for IWRM, neither climatic nor catchment models excel at predicting rare and brief events. This deficiency highlights why the assessment of predictive uncertainty should be an integral part of OMP modeling.

Effects of land use data on dry deposition in a regional photochemical model for eastern Texas.

PubMed

McDonald-Buller, E; Wiedinmyer, C; Kimura, Y; Allen, D

2001-08-01

Land use data are among the inputs used to determine dry deposition velocities for photochemical grid models such as the Comprehensive Air Quality Model with extensions (CAMx) that is currently used for attainment demonstrations and air quality planning by the state of Texas. The sensitivity of dry deposition and O3 mixing ratios to land use classification was investigated by comparing predictions based on default U.S. Geological Survey (USGS) land use data to predictions based on recently compiled land use data that were collected to improve biogenic emissions estimates. Dry deposition of O3 decreased throughout much of eastern Texas, especially in urban areas, with the new land use data. Predicted 1-hr averaged O3 mixing ratios with the new land use data were as much as 11 ppbv greater and 6 ppbv less than predictions based on USGS land use data during the late afternoon. In addition, the area with peak O3 mixing ratios in excess of 100 ppbv increased significantly in urban areas when deposition velocities were calculated based on the new land use data. Finally, more detailed data on land use within urban areas resulted in peak changes in O3 mixing ratios of approximately 2 ppbv. These results indicate the importance of establishing accurate, internally consistent land use data for photochemical modeling in urban areas in Texas. They also indicate the need for field validation of deposition rates in areas experiencing changing land use patterns, such as during urban reforestation programs or residential and commercial development.

Orbiter Landing Loads Math Model Description and Correlation with ALT Flight Data

NASA Technical Reports Server (NTRS)

Hamilton, D. A.; Schliesing, J. A.; Zupp, G. A., Jr.

1980-01-01

Results of the space shuttle approach and landing test are examined in order to assess landing gear characteristics and performance and verify landing dynamic analyses. The landing gears were instrumented with load-calibrated strain gages, a wheel-speed sensor, and strut stroke measurement devices. The mathematical procedure used in predicting the shuttle touchdown loads and dynamics is presented together with the comparisons between measured flight data and the analytical predictions. Conclusions from these data are also presented.

Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

NASA Astrophysics Data System (ADS)

Braun, A.; Hochschild, V.

2015-04-01

Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

The impact of land ownership, firefighting, and reserve status on fire probability in California

NASA Astrophysics Data System (ADS)

Starrs, Carlin Frances; Butsic, Van; Stephens, Connor; Stewart, William

2018-03-01

The extent of wildfires in the western United States is increasing, but how land ownership, firefighting, and reserve status influence fire probability is unclear. California serves as a unique natural experiment to estimate the impact of these factors, as ownership is split equally between federal and non-federal landowners; there is a relatively large proportion of reserved lands where extractive uses are prohibited and fire suppression is limited; and land ownership and firefighting responsibility are purposefully not always aligned. Panel Poisson regression techniques and pre-regression matching were used to model changes in annual fire probability from 1950-2015 on reserve and non-reserve lands on federal and non-federal ownerships across four vegetation types: forests, rangelands, shrublands, and forests without commercial species. Fire probability was found to have increased over time across all 32 categories. A marginal effects analysis showed that federal ownership and firefighting was associated with increased fire probability, and that the difference in fire probability on federal versus non-federal lands is increasing over time. Ownership, firefighting, and reserve status, played roughly equal roles in determining fire probability, and were found to have much greater influence than average maximum temperature (°C) during summer months (June, July, August), average annual precipitation (cm), and average annual topsoil moisture content by volume, demonstrating the critical role these factors play in western fire regimes and the importance of including them in future analysis focused on understanding and predicting wildfire in the Western United States.

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

A stochastic forest fire model for future land cover scenarios assessment

Treesearch

M. D' Andrea; P. Fiorucci; T.P. Holmes

2011-01-01

Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and...

Developmental changes of misconception and misperception of projectiles.

PubMed

Kim, In-Kyeong

2012-12-01

This study investigated the developmental changes of perceptual and cognitive commonsense physical knowledge. Children 4 to 9 years old (N = 156; 79 boys, 77 girls) participated. Each child was asked to predict the landing positions of balls that rolled down and fell off a virtual ramp and to choose the most natural-looking motion from different projectile motions depicted. The landing position of the most natural-looking projectile was compared with the predicted landing position and also compared with the actual landing position. The results showed children predicted the ball's landing position closer to the ramp than the actual position. Children also chose the depiction in which the ball fell closer to the ramp than the accurate position, although the error in the prediction task was larger than in the perception task and decreased with age. The results indicated the developmental convergence of explicit reasoning and implicit perception, which suggest a single knowledge system with representational re-description.

Modeling the potential persistence of various ecological systems under CMIP5 future climate and land use scenarios throughout California, USA

NASA Astrophysics Data System (ADS)

Baker, B.; Ferschweiler, K.; Bachelet, D. M.; Sleeter, B. M.

2016-12-01

California's geographic location, topographic complexity and latitudinal climatic gradient give rise to great biological and ecological diversity. However, increased land use pressure, altered seasonal weather patterns, and changes in temperature and precipitation regimes are having pronounced effects on ecosystems and the multitude of services they provide for an increasing population. As a result, natural resource managers are faced with formidable challenges to maintain these critical services. The goals of this project were to better understand how projected 21st century climate and land-use change scenarios may alter ecosystem dynamics, the spatial distribution of various vegetation types and land-use patterns, and to provide a coarse scale "triage map" of where land managers may want to concentrate efforts to reduce ecological stress in order to mitigate the potential impacts of a changing climate. We used the MC2 dynamic global vegetation model and the LUCAS state-and-transition simulation model to simulate the potential effects of future climate and land-use change on ecological processes for the state of California. Historical climate data were obtained from the PRISM dataset and nine CMIP5 climate models were run for the RCP 8.5 scenario. Climate projections were combined with a business-as-usual land-use scenario based on local-scale land use histories. For ease of discussion, results from five simulation runs (historic, hot-dry, hot-wet, warm-dry, and warm-wet) are presented. Results showed large changes in the extent of urban and agricultural lands. In addition, several simulated potential vegetation types persisted in situ under all four future scenarios, although alterations in total area, total ecosystem carbon, and forest vigor (NPP/LAI) were noted. As might be expected, the majority of the forested types that persisted occurred on public lands. However, more than 78% of the simulated subtropical mixed forest and 26% of temperate evergreen needleleaf forest types persisted on private lands under all four future scenarios. Result suggest that building collaborations across management borders could be valuable tool to guide natural resource management actions into the future.

Acoustic Prediction State of the Art Assessment

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

2007-01-01

The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction both for systems and components. These include semi-empirical, statistical, analytical, and numerical codes. System level results are shown for both aircraft and engines. Component level results are shown for a landing gear prototype, for fan broadband noise, for jet noise from a subsonic round nozzle, and for propulsion airframe aeroacoustic interactions. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.