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Sample records for hydrometeorological modeling land

  1. Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

    Science.gov (United States)

    Peters-Lidard, Christa D.

    2011-01-01

    The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling

  2. Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

    Science.gov (United States)

    Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

    2009-01-01

    The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by

  3. Spectral Behavior of a Linearized Land-Atmosphere Model: Applications to Hydrometeorology

    Science.gov (United States)

    Gentine, P.; Entekhabi, D.; Polcher, J.

    2008-12-01

    The present study develops an improved version of the linearized land-atmosphere model first introduced by Lettau (1951). This model is used to investigate the spectral response of land-surface variables to a daily forcing of incoming radiation at the land-surface. An analytical solution of the problem is found in the form of temporal Fourier series and gives the atmospheric boundary-layer and soil profiles of state variables (potential temperature, specific humidity, sensible and latent heat fluxes). Moreover the spectral dependency of surface variables is expressed as function of land-surface parameters (friction velocity, vegetation height, aerodynamic resistance, stomatal conductance). This original approach has several advantages: First, the model only requires little data to work and perform well: only time series of incoming radiation at the land-surface, mean specific humidity and temperature at any given height are required. These inputs being widely available over the globe, the model can easily be run and tested under various conditions. The model will also help analysing the diurnal shape and frequency dependency of surface variables and soil-ABL profiles. In particular, a strong emphasis is being placed on the explanation and prediction of Evaporative Fraction (EF) and Bowen Ratio diurnal shapes. EF is shown to remain a diurnal constant under restricting conditions: fair and dry weather, with strong solar radiation and no clouds. Moreover, the EF pseudo-constancy value is found and given as function of surface parameters, such as aerodynamic resistance and stomatal conductance. Then, application of the model for the conception of remote-sensing tools, according to the temporal resolution of the sensor, will also be discussed. Finally, possible extensions and improvement of the model will be discussed.

  4. Hydrometeorological network for flood monitoring and modeling

    Science.gov (United States)

    Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

    2013-08-01

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its

  5. Collaborative development of land use change scenarios for analysing hydro-meteorological risk

    Science.gov (United States)

    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

  6. HYDRO-METEOROLOGICAL CHARACTERISTICS FOR SUSTAINABLE LAND MANAGEMENT IN THE SINGKARAK BASIN, WEST SUMATRA

    Directory of Open Access Journals (Sweden)

    Kasdi Subagyono

    2008-11-01

    Full Text Available Studi tentang karakteristik hidro-meteorologi telah dilakukan di wilayah danau Singkarak pada 2006-2007 dengan melibatkan partisipasi masyarakat. Stasiun iklim otomatis dan pengukur tinggi muka air otomatis dipasang untuk memonitor data hidrologi dan meteorologi di wilayah cekungan Singkarak. Data meteorologi dianalisa untuk mengetahui karakteristik iklim di wilayah sekitar danau. Model hidrologi GR4J dan H2U diaplikasikan untuk simulasi discharge dan untuk mengkarakterisasi proses hidrologi di wilayah danau. Simulasi model aliran divalidasi pada musim hujan. Alternatif pengelolaan lahan diformulasikan berdasarkan karakteristik hidrologi daerah aliran sungai di sekitar cekungan Singkarak. Hasil penelitian menunjukkan bahwa daerah tangkapan di sekitar danau Singkarak memiliki respon yang tinggi terhadap jumlah dan intensitas hujan. Hidrograp menunjukkan peningkatan yang tajam dari discharge segera setelah curah hujan mulai dan menurun relative lamban ketika curah hujan berhenti. Untuk pengelolaan lahan secara berkelanjutan di wilayah danau Singkarak, konservasi lahan dan air harus menjadi prioritas utama. Wanatani dapat diimplementasikan sebagai alternatif sistem pertanaman oleh penduduk lokal. Karena potensi kelangkaan air bisa terjadi pada periode kering, panen air dan konservasi air dapat diterapkan sebagai opsi yang dapat dikombinasikan dalam sistem pengelolaan lahan.   Hydro-meteorological processes of the Singkarak basin has been studied involving participatory of local community in 2006-2007. Automatic weather station (AWS and automatic water level recorder (AWLR were installed to record meteorological and hydrological data within the Singkarak Basin. Meteorological data was analyzed to understand the meteorological characteristic surrounding the Basin area. Model of GR4J and H2U were used to simulated discharge and to understand the hydrological processes within the basin. The validation of simulated discharge was done in the wet season

  7. An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

    2007-01-01

    Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

  8. Optimal moment determination in POME-copula based hydrometeorological dependence modelling

    Science.gov (United States)

    Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

    2017-07-01

    Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

  9. Incorporating Sentinel-2-like remote sensing products in the hydrometeorological modelling over an agricultural area in south west France

    Science.gov (United States)

    Rivalland, Vincent; Gascoin, Simon; Etchanchu, Jordi; Coustau, Mathieu; Cros, Jérôme; Tallec, Tiphaine

    2016-04-01

    The Sentinel-2 mission will enable to monitor the land cover and the vegetation phenology at high-resolution (HR) every 5 days. However, current Land Surface Models (LSM) typically use land cover and vegetation parameters derived from previous low to mid resolution satellite missions. Here we studied the effect of introducing Sentinel-2-like data in the simulation of the land surface energy and water fluxes in a region dominated by cropland. Simulations were performed with the ISBA-SURFEX LSM, which is used in the operational hydrometeorological chain of Meteo-France for hydrological forecasts and drought monitoring. By default, SURFEX vegetation land surface parameters and temporal evolution are from the ECOCLIMAP II European database mostly derived from MODIS products at 1 km resolution. The model was applied to an experimental area of 30 km by 30 km in south west France. In this area the resolution of ECOCLIMAP is coarser than the typical size of a crop field. This means that several crop types can be mixed in a pixel. In addition ECOCLIMAP provides a climatology of the vegetation phenology and thus does not account for the interannual effects of the climate and land management on the crop growth. In this work, we used a series of 26 Formosat-2 images at 8-m resolution acquired in 2006. From this dataset, we derived a land cover map and a leaf area index map (LAI) at each date, which were substituted to the ECOCLIMAP land cover map and the LAI maps. The model output water and energy fluxes were compared to a standard simulation using ECOCLIMAP only and to in situ measurements of soil moisture, latent and sensible heat fluxes. The results show that the introduction of the HR products improved the timing of the evapotranspiration. The impact was the most visible on the crops having a growing season in summer (maize, sunflower), because the growth period is more sensitive to the climate.

  10. Toward Improving Predictability of Extreme Hydrometeorological Events: the Use of Multi-scale Climate Modeling in the Northern High Plains

    Science.gov (United States)

    Munoz-Arriola, F.; Torres-Alavez, J.; Mohamad Abadi, A.; Walko, R. L.

    2014-12-01

    Our goal is to investigate possible sources of predictability of hydrometeorological extreme events in the Northern High Plains. Hydrometeorological extreme events are considered the most costly natural phenomena. Water deficits and surpluses highlight how the water-climate interdependence becomes crucial in areas where single activities drive economies such as Agriculture in the NHP. Nonetheless we recognize the Water-Climate interdependence and the regulatory role that human activities play, we still grapple to identify what sources of predictability could be added to flood and drought forecasts. To identify the benefit of multi-scale climate modeling and the role of initial conditions on flood and drought predictability on the NHP, we use the Ocean Land Atmospheric Model (OLAM). OLAM is characterized by a dynamic core with a global geodesic grid with hexagonal (and variably refined) mesh cells and a finite volume discretization of the full compressible Navier Stokes equations, a cut-grid cell method for topography (that reduces error in computational gradient computation and anomalous vertical dispersion). Our hypothesis is that wet conditions will drive OLAM's simulations of precipitation to wetter conditions affecting both flood forecast and drought forecast. To test this hypothesis we simulate precipitation during identified historical flood events followed by drought events in the NHP (i.e. 2011-2012 years). We initialized OLAM with CFS-data 1-10 days previous to a flooding event (as initial conditions) to explore (1) short-term and high-resolution and (2) long-term and coarse-resolution simulations of flood and drought events, respectively. While floods are assessed during a maximum of 15-days refined-mesh simulations, drought is evaluated during the following 15 months. Simulated precipitation will be compared with the Sub-continental Observation Dataset, a gridded 1/16th degree resolution data obtained from climatological stations in Canada, US, and

  11. Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

    Science.gov (United States)

    2015-09-21

    rain gauges to measure precipitation , and 1 internal mini-flume to measure runoff . 9 Fig. 8. Processed fluxes measured at the two eddy...SECURITY CLASSIFICATION OF: Arid and semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface...semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface conditions, including soil moisture

  12. Mathematical Modelling of Thermal Process to Aquatic Environment with Different Hydrometeorological Conditions

    Directory of Open Access Journals (Sweden)

    Alibek Issakhov

    2014-01-01

    Full Text Available This paper presents the mathematical model of the thermal process from thermal power plant to aquatic environment of the reservoir-cooler, which is located in the Pavlodar region, 17 Km to the north-east of Ekibastuz town. The thermal process in reservoir-cooler with different hydrometeorological conditions is considered, which is solved by three-dimensional Navier-Stokes equations and temperature equation for an incompressible flow in a stratified medium. A numerical method based on the projection method, divides the problem into three stages. At the first stage, it is assumed that the transfer of momentum occurs only by convection and diffusion. Intermediate velocity field is solved by fractional steps method. At the second stage, three-dimensional Poisson equation is solved by the Fourier method in combination with tridiagonal matrix method (Thomas algorithm. Finally, at the third stage, it is expected that the transfer is only due to the pressure gradient. Numerical method determines the basic laws of the hydrothermal processes that qualitatively and quantitatively are approximated depending on different hydrometeorological conditions.

  13. Developing the Model for the GIS Applications in National Hydro-Meteorological Service in Poland

    Science.gov (United States)

    Kubacka, D.; Barszczynska, M.; Madej, P.

    2003-04-01

    historic data access. These layers are also sufficient for a hydro-meteorological situation visualisations suitable for the country and division maps. The existing data and thematic layers were used to develop an Internet service providing the information concerning the hydro-meteorological posts. It also allowed presenting the results of the numerical weather forecast model in the Internet. It is planned to perform the visualisation of the hydro-meteorological phenomena in the monthly IMWM bulletin.

  14. Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

    Directory of Open Access Journals (Sweden)

    E. Picciotti

    2013-05-01

    Full Text Available Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative mbox{integrated} decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5

  15. Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

    Science.gov (United States)

    Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

    2015-07-01

    This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

  16. Spatiotemporal variability of water and energy fluxes: TERENO- prealpine hydrometeorological data analysis and inverse modeling with GEOtop and PEST

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    Soltani, M.; Kunstmann, H.; Laux, P.; Mauder, M.

    2016-12-01

    In mountainous and prealpine regions echohydrological processes exhibit rapid changes within short distances due to the complex orography and strong elevation gradients. Water- and energy fluxes between the land surface and the atmosphere are crucial drivers for nearly all ecosystem processes. The aim of this research is to analyze the variability of surface water- and energy fluxes by both comprehensive observational hydrometeorological data analysis and process-based high resolution hydrological modeling for a mountainous and prealpine region in Germany. We particularly focus on the closure of the observed energy balance and on the added value of energy flux observations for parameter estimation in our hydrological model (GEOtop) by inverse modeling using PEST. Our study area is the catchment of the river Rott (55 km2), being part of the TERENO prealpine observatory in Southern Germany, and we focus particularly on the observations during the summer episode May to July 2013. We present the coupling of GEOtop and the parameter estimation tool PEST, which is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. Estimation of the surface energy partitioning during the data analysis process revealed that the latent heat flux was considered as the main consumer of available energy. The relative imbalance was largest during nocturnal periods. An energy imbalance was observed at the eddy-covariance site Fendt due to either underestimated turbulent fluxes or overestimated available energy. The calculation of the simulated energy and water balances for the entire catchment indicated that 78% of net radiation leaves the catchment as latent heat flux, 17% as sensible heat, and 5% enters the soil in the form of soil heat flux. 45% of the catchment aggregated precipitation leaves the catchment as discharge and 55% as evaporation. Using the developed GEOtop-PEST interface, the hydrological model is calibrated by comparing

  17. Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

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    Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

    2017-10-01

    This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

  18. Combined use of local and global hydrometeorological data with regional and global hydrological models in the Magdalena - Cauca river basin, Colombia

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    Rodriguez, Erasmo; Sanchez, Ines; Duque, Nicolas; Lopez, Patricia; Kaune, Alexander; Werner, Micha; Arboleda, Pedro

    2017-04-01

    The Magdalena Cauca Macrobasin (MCMB) in Colombia, with an area of about 257,000 km2, is the largest and most important water resources system in the country. With almost 80% of the Colombian population (46 million people) settled in the basin, it is the main source of water for demands including human consumption, agriculture, hydropower generation, industrial activities and ecosystems. Despite its importance, the basin has witnessed enormous changes in land-cover and extensive deforestation during the last three decades. To make things more complicated, the MCMB currently lacks a set of tools to support planning and decision making processes at scale of the whole watershed. Considering this, the MCMB has been selected as one of the six different regional case studies in the eartH2Observe research project, in which hydrological and meteorological reanalysis products are being validated for the period 1980-2012. The combined use of the hydrological and meteorological reanalysis data, with local hydrometeorological data (precipitation, temperature and streamflow) provided by the National Hydrometeorological Agency (IDEAM), has given us the opportunity to implement and test three hydrological models (VIC, WFLOW and a Water Balance Model based on the Budyko framework) at the basin scale. Additionally, results from the global models in the eartH2Observe hydrological reanalysis have been used to evaluate their performance against the observed streamflow data. This paper discusses the comparison between streamflow observations and simulations from the global hydrological models forced with the WFDEI data, and regional models forced with a combination of observed and meteorological reanalysis data, in the whole domain of the MCMB. For the three regional models analysed results show good performances for some sub-basins and poor performances for others. This can be due to the smoothing of the precipitation fields, interpolated from point daily rainfall data, the effect of

  19. Hydrometeorological Automated Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Office of Hydrologic Development of the National Weather Service operates HADS, the Hydrometeorological Automated Data System. This data set contains the last 48...

  20. The hydrometeorological implications of zoning laws: Can land use regulations of urban density and sprawl improve a city's resilience?

    Science.gov (United States)

    Bou-Zeid, E.; Ryu, Y. H.; Smith, J. A.; Newburn, D. A.

    2015-12-01

    The intensification of heat waves and of the hydrological cycle due to global climate change pose particularly high risks to urban residents. Cities are already hotter than their surroundings due to the urban heat island effect and are known to result in local intensification of rainfall and flooding due to their coupled impacts on the surface and the lower atmosphere. These interacting local and global changes can adversely affect the health and well being of urban residents, and city administrators are increasing efforts to mitigate and adapt to the potential disruptions though various infrastructure and preparedness programs. However, as cities worldwide continue to expand, a key decision is how to manage that urban sprawl and regulate its spatial features to aid in the mitigation and adaptation effort. This study assesses whether alternative zoning regulations that modify the density and extent of a metropolitan region, but have a minimal impact on total population and demographic growth, have an appreciable impact on its response to extreme weather events, and as such, whether they can be used to increase urban resilience. We consider Baltimore (the city and its surrounding suburbs), which in 1967 adopted one of the first urban growth boundaries (UGBs) in the United States, as our test case. Departing from the urban extent circa 1900, we create alternative land use patterns that, compared to the actual current land use baseline, would have resulted from drastically different policy scenarios and approaches to zoning that the city would have undertaken. We consider various alternatives where the city is smaller and denser, due to stricter regulation, versus larger and less dense than the actual baseline, while maintaining the same total population. Our findings indicate that lower densities have significant benefits: compared to the current landscape and to denser patterns, they reduce both extreme temperatures during heat waves and spatio-temporal rainfall

  1. A hydro-meteorological model chain to assess the influence of natural variability and impacts of climate change on extreme events and propose optimal water management

    Science.gov (United States)

    von Trentini, F.; Willkofer, F.; Wood, R. R.; Schmid, F. J.; Ludwig, R.

    2017-12-01

    The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. Therefore, a hydro-meteorological model chain is applied. It employs high performance computing capacity of the Leibniz Supercomputing Centre facility SuperMUC to dynamically downscale 50 members of the Global Circulation Model CanESM2 over European and Eastern North American domains using the Canadian Regional Climate Model (RCM) CRCM5. Over Europe, the unique single model ensemble is conjointly analyzed with the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change in the dynamics of extreme events. Furthermore, these 50 members of a single RCM will enhance extreme value statistics (extreme return periods) by exploiting the available 1500 model years for the reference period from 1981 to 2010. Hence, the RCM output is applied to drive the process based, fully distributed, and deterministic hydrological model WaSiM in high temporal (3h) and spatial (500m) resolution. WaSiM and the large ensemble are further used to derive a variety of hydro-meteorological patterns leading to severe flood events. A tool for virtual perfect prediction shall provide a combination of optimal lead time and management strategy to mitigate certain flood events following these patterns.

  2. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM project

    Directory of Open Access Journals (Sweden)

    A. Hally

    2015-03-01

    Full Text Available The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB, an innovative software component developed within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS and HBV to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH and AROME and a downscaling algorithm (RainFARM in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus giving a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (> 1500. The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash flood early-warning perspective.

  3. Ensemble Analysis of Variational Assimilation of Hydrologic and Hydrometeorological Data into Distributed Hydrologic Model

    Science.gov (United States)

    Lee, H.; Seo, D.; Koren, V.

    2008-12-01

    A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.

  4. Modeling detailed hydro-meteorological surfaces and runoff response in large diverse watersheds

    International Nuclear Information System (INIS)

    Byrne, J.; Kienzle, S.W.; MacDonald, R.J.

    2008-01-01

    An understanding of local variability in climatic conditions over complex terrain is imperative to making accurate assessments of impacts from climate change on fresh water ecosystems (Daly, 2006). The derivation of representative spatial data in diverse environments poses a significant challenge to the modelling community. This presentation describes the current status of a long term ongoing hydro-climate model development program. We are developing a gridded hydroclimate dataset for diverse watersheds using SimGrid (Larson, 2008; Lapp et al., 2005; Sheppard, 1996), a model that applies the Mountain Climate Model (MTCLIM; Hungerford et al., 1989) to simulate hydro-climatic conditions over diverse terrain. The model uses GIS based terrain categories (TC) classified by slope, aspect, elevation, and soil water storage. SimGrid provides daily estimates of solar radiation, air temperature, relative humidity, precipitation, snowpack and soil water storage over space. Earlier versions of the model have been applied in the St. Mary (Larson, 2008) and upper Oldman basins (Lapp et al., 2005), giving realistic estimates of hydro-climatic variables. The current study demonstrates improvements to the estimation of temperature, precipitation, snowpack, soil water storage and runoff from the basin. Soil water storage data for the upper drainage were derived with GIS and included in SimGrid to estimate soil water flux over the time period. These changes help improve the estimation of spatial climatic variability over the basin while accounting for topographical influence. In further work we will apply spatial hydro-climatic surfaces from the SimGrid model to assess the hydrologic response to environmental change for watersheds in Canada and beyond. (author)

  5. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    KAUST Repository

    El-Samra, R.

    2017-02-15

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  6. Improved cyberinfrastructure for integrated hydrometeorological predictions within the fully-coupled WRF-Hydro modeling system

    Science.gov (United States)

    gochis, David; hooper, Rick; parodi, Antonio; Jha, Shantenu; Yu, Wei; Zaslavsky, Ilya; Ganapati, Dinesh

    2014-05-01

    The community WRF-Hydro system is currently being used in a variety of flood prediction and regional hydroclimate impacts assessment applications around the world. Despite its increasingly wide use certain cyberinfrastructure bottlenecks exist in the setup, execution and post-processing of WRF-Hydro model runs. These bottlenecks result in wasted time, labor, data transfer bandwidth and computational resource use. Appropriate development and use of cyberinfrastructure to setup and manage WRF-Hydro modeling applications will streamline the entire workflow of hydrologic model predictions. This talk will present recent advances in the development and use of new open-source cyberinfrastructure tools for the WRF-Hydro architecture. These tools include new web-accessible pre-processing applications, supercomputer job management applications and automated verification and visualization applications. The tools will be described successively and then demonstrated in a set of flash flood use cases for recent destructive flood events in the U.S. and in Europe. Throughout, an emphasis on the implementation and use of community data standards for data exchange is made.

  7. Ecosystem functioning is enveloped by hydrometeorological variability.

    Science.gov (United States)

    Pappas, Christoforos; Mahecha, Miguel D; Frank, David C; Babst, Flurin; Koutsoyiannis, Demetris

    2017-09-01

    Terrestrial ecosystem processes, and the associated vegetation carbon dynamics, respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Long-term variability of the terrestrial carbon cycle is not yet well constrained and the resulting climate-biosphere feedbacks are highly uncertain. Here we present a comprehensive overview of hydrometeorological and ecosystem variability from hourly to decadal timescales integrating multiple in situ and remote-sensing datasets characterizing extra-tropical forest sites. We find that ecosystem variability at all sites is confined within a hydrometeorological envelope across sites and timescales. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. However, simulation results with state-of-the-art process-based models do not reflect this long-term persistent behaviour in ecosystem functioning. Accordingly, we develop a cross-time-scale stochastic framework that captures hydrometeorological and ecosystem variability. Our analysis offers a perspective for terrestrial ecosystem modelling and paves the way for new model-data integration opportunities in Earth system sciences.

  8. Evaluation of regional-scale water level simulations using various river routing schemes within a hydrometeorological modelling framework for the preparation of the SWOT mission

    Science.gov (United States)

    Häfliger, V.; Martin, E.; Boone, A. A.; Habets, F.; David, C. H.; Garambois, P. A.; Roux, H.; Ricci, S. M.; Thévenin, A.; Berthon, L.; Biancamaria, S.

    2014-12-01

    The ability of a regional hydrometeorological model to simulate water depth is assessed in order to prepare for the SWOT (Surface Water and Ocean Topography) mission that will observe free surface water elevations for rivers having a width larger than 50/100 m. The Garonne river (56 000 km2, in south-western France) has been selected owing to the availability of operational gauges, and the fact that different modeling platforms, the hydrometeorological model SAFRAN-ISBA-MODCOU and several fine scale hydraulic models, have been extensively evaluated over two reaches of the river. Several routing schemes, ranging from the simple Muskingum method to time-variable parameter kinematic and diffusive waves schemes with time varying parameters, are tested using predetermined hydraulic parameters. The results show that the variable flow velocity scheme is advantageous for discharge computations when compared to the original Muskingum routing method. Additionally, comparisons between water level computations and in situ observations led to root mean square errors of 50-60 cm for the improved Muskingum method and 40-50 cm for the kinematic-diffusive wave method, in the downstream Garonne river. The error is larger than the anticipated SWOT resolution, showing the potential of the mission to improve knowledge of the continental water cycle. Discharge computations are also shown to be comparable to those obtained with high-resolution hydraulic models over two reaches. However, due to the high variability of river parameters (e.g. slope and river width), a robust averaging method is needed to compare the hydraulic model outputs and the regional model. Sensitivity tests are finally performed in order to have a better understanding of the mechanisms which control the key hydrological processes. The results give valuable information about the linearity, Gaussianity and symetry of the model, in order to prepare the assimilation of river heights in the model.

  9. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... temperature are explored in a multi-objective calibration experiment to optimize the parameters in a SVAT model in the Sahel. The two satellite derived variables were effective at constraining most land-surface and soil parameters. A data assimilation framework is developed and implemented with an integrated...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...

  10. GLEAM version 3: Global Land Evaporation Datasets and Model

    Science.gov (United States)

    Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

    2015-12-01

    Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

  11. Hydrometeorological daily recharge assessment model (DREAM) for the Western Mountain Aquifer, Israel: Model application and effects of temporal patterns

    Science.gov (United States)

    Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Navon, S.; Frumkin, A.; Morin, E.

    2010-05-01

    Recharge is a critical issue for water management. Recharge assessment and the factors affecting recharge are of scientific and practical importance. The purpose of this study was to develop a daily recharge assessment model (DREAM) on the basis of a water balance principle with input from conventional and generally available precipitation and evaporation data and demonstrate the application of this model to recharge estimation in the Western Mountain Aquifer (WMA) in Israel. The WMA (area 13,000 km2) is a karst aquifer that supplies 360-400 Mm3 yr-1 of freshwater, which constitutes 20% of Israel's freshwater and is highly vulnerable to climate variability and change. DREAM was linked to a groundwater flow model (FEFLOW) to simulate monthly hydraulic heads and spring flows. The models were calibrated for 1987-2002 and validated for 2003-2007, yielding high agreement between calculated and measured values (R2 = 0.95; relative root-mean-square error = 4.8%; relative bias = 1.04). DREAM allows insights into the effect of intra-annual precipitation distribution factors on recharge. Although annual precipitation amount explains ˜70% of the variability in simulated recharge, analyses with DREAM indicate that the rainy season length is an important factor controlling recharge. Years with similar annual precipitation produce different recharge values as a result of temporal distribution throughout the rainy season. An experiment with a synthetic data set exhibits similar results, explaining ˜90% of the recharge variability. DREAM represents significant improvement over previous recharge estimation techniques in this region by providing near-real-time recharge estimates that can be used to predict the impact of climate variability on groundwater resources at high temporal and spatial resolution.

  12. Assessing Nature-Based Coastal Protection against Disasters Derived from Extreme Hydrometeorological Events in Mexico

    Directory of Open Access Journals (Sweden)

    Octavio Pérez-Maqueo

    2018-04-01

    Full Text Available Natural ecosystems are expected to reduce the damaging effects of extreme hydrometeorological effects. We tested this prediction for Mexico by performing regression models, with two dependent variables: the occurrence of deaths and economic damages, at a state and municipality levels. For each location, the explanatory variables were the Mexican social vulnerability index (which includes socioeconomic aspects, local capacity to prevent and respond to an emergency, and the perception of risk and land use cover considering different vegetation types. We used the hydrometeorological events that have affected Mexico from 1970 to 2011. Our findings reveal that: (a hydrometeorological events affect both coastal and inland states, although damages are greater on the coast; (b the protective role of natural ecosystems only was clear at a municipality level: the presence of mangroves, tropical dry forest and tropical rainforest was related to a significant reduction in the occurrence of casualties. Social vulnerability was positively correlated with the occurrence of deaths. Natural ecosystems, both typically coastal (mangroves and terrestrial (tropical forests, which are located on the mountain ranges close to the coast function for storm protection. Thus, their conservation and restoration are effective and sustainable strategies that will help protect and develop the increasingly urbanized coasts.

  13. OPAL Netlogo Land Condition Model

    Science.gov (United States)

    2014-08-15

    ER D C/ CE RL T R- 14 -1 2 Optimal Allocation of Land for Training and Non-training Uses ( OPAL ) OPAL Netlogo Land Condition Model...Fulton, Natalie Myers, Scott Tweddale, Dick Gebhart, Ryan Busby, Anne Dain-Owens, and Heidi Howard August 2014 OPAL team measuring above and...online library at http://acwc.sdp.sirsi.net/client/default. Optimal Allocation of Land for Training and Non-training Uses ( OPAL ) ERDC/CERL TR-14-12

  14. The Mexican hydro-meteorological disasters and climate network (redesclim) as model on outreach decision makers on disaster public policy in Mexico.

    Science.gov (United States)

    Welsh-Rodriguez, C. M.; Rodriguez-Estevez, J. M., Sr.; Romo-Aguilar, M. D. L.; Brito-Castillo, L.; Salinas-Prieto, A.; Gonzalez-Sosa, E.; Pérez-Campuzano, E.

    2017-12-01

    REDESCLIM was designed and develop in 2011 due to a public call from The Science and Technology Mexican Council (CONACYT); CONACYT lead the activities for its organization and development among the academic community. REDESCLIM was created to enhance the capacity of response to hydro-meteorological disasters and climate events through an integrative effort of researchers, technologists, entrepreneurs, politicians and society. Brief summary of our objectives: 1) Understand the causes of disasters, to reduce risks to society and ecosystems 2) Support research and interdisciplinary assessment of the physical processes in natural and social phenomena to improve understanding of causes and impacts 3) Strengths collaboration with academic, government, private and other interdisciplinary networks from Mexico and other countries 4) Build human capacity and promote the development of skills 5) Recommend strategies for climate hazard prevention, mitigation and response, especially for hazard with the greatest impacts in Mexico, such as hurricanes, floods, drought, wild fires and other extremes events. We provide a continues communication channel on members research results to provide scientific information that could be used for different proposes, specificaly for decision makers who are dealing with ecological and hydro meteorological problems that can result in disasters, and provide a services menu based on the members scientific projects, publications, teaching courses, in order to impact public policy as final result. http://www.redesclim.org.mx. So far we have some basic results: Fiver national meetings (participants from 35 countries around the world), 7 Workshops and seminars (virtual and in-person), Climatic data platforms ( http://clicom.mex.cicese.mx, http://clicom-mex.cicese.mx/malla, http://atlasclimatico.unam.mx/REDESCLIM2/ ), climate change scenarios for the general public at http://escenarios.inecc.gob.mx, 14 seed projects, one model to hurricane simulation

  15. Simulating feedbacks in land use and land cover change models

    NARCIS (Netherlands)

    Verburg, P.H.

    2006-01-01

    In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore

  16. A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

    Science.gov (United States)

    Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin

    2017-12-01

    Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

  17. Multiparameter models in the management of the development of territories, taking into account the influence of hydrometeorological factors

    Science.gov (United States)

    Istomin, E. P.; Popov, N. N.; Sokolov, A. G.; Fokicheva, A. A.

    2018-01-01

    The article considers the geoinformation management of the territory as a way to manage the organizational and technical systems and territories distributed in space. The article describes the main factors for the development and implementation of management decisions, requirements for the territorial management system and the structure of knowledge and data. Mathematical one-parameter and multiparameter models of risk assessment of management decisions applied to the natural and climatic potential of the development of the territory were considered.

  18. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... by the hydrological model is found to be insensitive to model resolution. Furthermore, this study highlights the effect of bias precipitation by regional climate model and it implications for hydrological modelling....

  19. Hydrometeorological Research in South Africa: A Review

    Directory of Open Access Journals (Sweden)

    Christina M. Botai

    2015-04-01

    Full Text Available Water resources, particularly in arid and semi-arid regions of the world are of great concern, as they are closely linked to the wellbeing of humankind. Sophisticated hydrological prediction tools are required to assess climatic and hydrometeorological conditions, as they impact the sustainability of water resources as well as water availability. Research and data collection activities from multi-hydrometeorological sensors (e.g., gauges, radars, satellites form the basis for quantifying the impact of extreme episodes along the hydrologic phases that manifest in terms of the magnitude, duration and frequency of floods, droughts and other hydrometeorological hazards that affect water resources management. A number of hydrometeorological research activities have been reported in the literature by various researchers and research groups globally. This contribution presents (a a review of the hydrometeorology resource landscape in South Africa; (b an analysis of the hydrometeorology services and products in South Africa; (c a review of the hydrometeorological research that has been conducted in South Africa for the last four decades; and (d highlights on some of the challenges facing the sustained advancement of research in hydrometeorology in South Africa.

  20. Joint System of the National Hydrometeorology for disaster prevention

    Science.gov (United States)

    Lim, J.; Cho, K.; Lee, Y. S.; Jung, H. S.; Yoo, H. D.; Ryu, D.; Kwon, J.

    2014-12-01

    Hydrological disaster relief expenditure accounts for as much as 70 percent of total expenditure of disasters occurring in Korea. Since the response to and recovery of disasters are normally based on previous experiences, there have been limitations when dealing with ever-increasing localized heavy rainfall with short range in the era of climate change. Therefore, it became necessary to establish a system that can respond to a disaster in advance through the analysis and prediction of hydrometeorological information. Because a wide range of big data is essential, it cannot be done by a single agency only. That is why the three hydrometeorology-related agencies cooperated to establish a pilot (trial) system at Soemjingang basin in 2013. The three governmental agencies include the National Emergency Management Agency (NEMA) in charge of disaster prevention and public safety, the National Geographic Information Institute (NGII under Ministry of Land, Infrastructure and Transport) in charge of geographical data, and the Korea Meteorological Administration (KMA) in charge of weather information. This pilot system was designed to be able to respond to disasters in advance through providing a damage prediction information for flash flood to public officers for safety part using high resolution precipitation prediction data provided by the KMA and high precision geographic data by NGII. To produce precipitation prediction data with high resolution, the KMA conducted downscaling from 25km×25km global model to 3km×3km local model and is running the local model twice a day. To maximize the utility of weather prediction information, the KMA is providing the prediction information for 7 days with 1 hour interval at Soemjingang basin to monitor and predict not only flood but also drought. As no prediction is complete without a description of its uncertainty, it is planned to continuously develop the skills to improve the uncertainty of the prediction on weather and its impact

  1. Multifractal Conceptualisation of Hydro-Meteorological Extremes

    Science.gov (United States)

    Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

    2009-04-01

    Hydrology and more generally sciences involved in water resources management, technological or operational developments face a fundamental difficulty: the extreme variability of hydro-meteorological fields. It clearly appears today that this variability is a function of the observation scale and yield hydro-meteorological hazards. Throughout the world, the development of multifractal theory offers new techniques for handling such non-classical variability over wide ranges of time and space scales. The resulting stochastic simulations with a very limited number of parameters well reproduce the long range dependencies and the clustering of rainfall extremes often yielding fat tailed (i.e., an algebraic type) probability distributions. The goal of this work was to investigate the ability of using very short or incomplete data records for reliable statistical predictions of the extremes. In particular we discuss how to evaluate the uncertainty in the empirical or semi-analytical multifractal outcomes. We consider three main aspects of the evaluation, such as the scaling adequacy, the multifractal parameter estimation error and the quantile estimation error. We first use the multiplicative cascade model to generate long series of multifractal data. The simulated samples had to cover the range of the universal multifractal parameters widely available in the scientific literature for the rainfall and river discharges. Using these long multifractal series and their sub-samples, we defined a metric for parameter estimation error. Then using the sets of estimated parameters, we obtained the quantile values for a range of excedance probabilities from 5% to 0.01%. Plotting the error bars on a quantile plot enable an approximation of confidence intervals that would be particularly important for the predictions of multifractal extremes. We finally illustrate the efficiency of such concept on its application to a large database (more than 16000 selected stations over USA and

  2. How Are Feedbacks Represented in Land Models?

    Directory of Open Access Journals (Sweden)

    Yang Chen

    2016-09-01

    Full Text Available Land systems are characterised by many feedbacks that can result in complex system behaviour. We defined feedbacks as the two-way influences between the land use system and a related system (e.g., climate, soils and markets, both of which are encompassed by the land system. Land models that include feedbacks thus probably more accurately mimic how land systems respond to, e.g., policy or climate change. However, representing feedbacks in land models is a challenge. We reviewed articles incorporating feedbacks into land models and analysed each with predefined indicators. We found that (1 most modelled feedbacks couple land use systems with transport, soil and market systems, while only a few include feedbacks between land use and social systems or climate systems; (2 equation-based land use models that follow a top-down approach prevail; and (3 feedbacks’ effects on system behaviour remain relatively unexplored. We recommend that land system modellers (1 consider feedbacks between land use systems and social systems; (2 adopt (bottom-up approaches suited to incorporating spatial heterogeneity and better representing land use decision-making; and (3 pay more attention to nonlinear system behaviour and its implications for land system management and policy.

  3. Land cover change or land use intensification: simulating land system change with a global-scale land change model

    NARCIS (Netherlands)

    van Asselen, S.; Verburg, P.H.

    2013-01-01

    Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land

  4. Central Asian Snow Cover from Hydrometeorological Surveys

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Central Asian Snow Cover from Hydrometeorological Surveys data are based on observations made by personnel for three river basins: Amu Darya, Sir Darya, and...

  5. Modelling land degradation in IMAGE 2

    NARCIS (Netherlands)

    Hootsmans RM; Bouwman AF; Leemans R; Kreileman GJJ; MNV

    2001-01-01

    Food security may be threatened by loss of soil productivity as a result of human-induced land degradation. Water erosion is the most important cause of land degradation, and its effects are irreversible. This report describes the IMAGE land degradation model developed for describing current and

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

    Science.gov (United States)

    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.

  7. Land-use change arising from rural land exchange : an agent-based simulation model

    NARCIS (Netherlands)

    Bakker, Martha M.; Alam, Shah Jamal; van Dijk, Jerry|info:eu-repo/dai/nl/29612642X; Rounsevell, Mark D. A.

    Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

  8. The Land Administration Domain Model

    NARCIS (Netherlands)

    Lemmen, C.; Van Oosterom, P.J.M.; Bennett, R.

    2015-01-01

    Societal drivers including poverty eradication, gender equality, indigenous recognition, adequate housing, sustainable agriculture, food security, climate change response, and good governance, influence contemporary land administration design. Equally, the opportunities provided by technological

  9. Fuzzy optimization model for land use change

    OpenAIRE

    L. Jahanshahloo; E. Haghi

    2014-01-01

    There are some important questions in Land use change literature, for instance How much land to allocate to each of a number of land use type in order to maximization of (household or individual) rent -paying ability, minimization of environmental impacts or maximization of population income. In this paper, we want to investigate them and propose mathematical models to find an answer for these questions. Since Most of the parameters in this process are linguistics and fuzzy logic is a powerfu...

  10. A framework for benchmarking land models

    Directory of Open Access Journals (Sweden)

    Y. Q. Luo

    2012-10-01

    Full Text Available Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1 targeted aspects of model performance to be evaluated, (2 a set of benchmarks as defined references to test model performance, (3 metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4 model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1 a priori thresholds of acceptable model performance and (2 a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties

  11. ICT-based hydrometeorology science and natural disaster societal impact assessment

    Science.gov (United States)

    Parodi, A.; Clematis, A.; Craig, G. C.; Kranzmueller, D.

    2009-09-01

    In the Lisbon strategy, the 2005 European Council identified knowledge and innovation as the engines of sustainable growth and stated that it is essential to build a fully inclusive information society. In parallel, the World Conference on Disaster Reduction (Hyogo, 2005), defined among its thematic priorities the improvement of international cooperation in hydrometeorology research activities. This was recently confirmed at the joint press conference of the Center for Research on Epidemiology of Disasters (CRED) with the United Nations International Strategy for Disaster Reduction (UNISDR) Secretariat, held on January 2009, where it was noted that flood and storm events are among the natural disasters that most impact human life. Hydrometeorological science has made strong progress over the last decade at the European and worldwide level: new modelling tools, post processing methodologies and observational data are available. Recent European efforts in developing a platform for e-science, like EGEE (Enabling Grids for E-sciencE), SEE-GRID-SCI (South East Europe GRID e-Infrastructure for regional e-Science), and the German C3-Grid, provide an ideal basis for the sharing of complex hydrometeorological data sets and tools. Despite these early initiatives, however, the awareness of the potential of the Grid technology as a catalyst for future hydrometeorological research is still low and both the adoption and the exploitation have astonishingly been slow, not only within individual EC member states, but also on a European scale. With this background in mind, the goal of the Distributed Research Infrastructure for Hydro-Meteorology Study (DRIHMS) project is the promotion of the Grid culture within the European hydrometeorological research community through the diffusion of a Grid platform for e-collaboration in this earth science sector: the idea is to further boost European research excellence and competitiveness in the fields of hydrometeorological research and Grid

  12. Advances in land modeling of KIAPS based on the Noah Land Surface Model

    Science.gov (United States)

    Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

    2017-08-01

    As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

  13. Land Use Change Modelling in R

    Science.gov (United States)

    Moulds, S.; Buytaert, W.

    2014-12-01

    Land use activities, through the provision of natural resources, are essential to human existence. In many regions land use change is degrading biodiversity and threatening the sustainability of ecosystem services upon which communities and livelihoods depend. Spatially explicit land use change models are widely used to understand and quantify key processes that affect land use change and make predictions about past and future change. These models typically include a module to estimate the suitability of different locations to particular land use types based on biophysical and socioeconomic predictor variables and a module to allocate change spatially. They are commonly implemented in languages such as C/C++ and Fortran and made available as standalone applications or through proprietary GIS. In many cases the models are released under closed source licences, limiting the reproducibility of scientific results and making model comparison difficult. This work presents a new R package providing methods and classes to support land use change modelling and model development and comparison within the open source R statistical computing environment. The package makes use of existing R implementations of methods such as random forests and recursive partitioning and regression trees to estimate location suitability, as well as providing methods for statistical model building and evaluation. Currently two spatial allocation methods are provided: the first based on the widely used and tested CLUE-S algorithm and the second a novel stochastic procedure developed for large scale applications. Some common tools for evaluating allocation results are implemented. It is hoped that the package will provide a framework for the development of new routines that can be incorporated into future releases of the code.

  14. The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

    Science.gov (United States)

    Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

    2013-01-01

    The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  15. Identifying and Evaluating Chaotic Behavior in Hydro-Meteorological Processes

    Directory of Open Access Journals (Sweden)

    Soojun Kim

    2015-01-01

    Full Text Available The aim of this study is to identify and evaluate chaotic behavior in hydro-meteorological processes. This study poses the two hypotheses to identify chaotic behavior of the processes. First, assume that the input data is the significant factor to provide chaotic characteristics to output data. Second, assume that the system itself is the significant factor to provide chaotic characteristics to output data. For solving this issue, hydro-meteorological time series such as precipitation, air temperature, discharge, and storage volume were collected in the Great Salt Lake and Bear River Basin, USA. The time series in the period of approximately one year were extracted from the original series using the wavelet transform. The generated time series from summation of sine functions were fitted to each series and used for investigating the hypotheses. Then artificial neural networks had been built for modeling the reservoir system and the correlation dimension was analyzed for the evaluation of chaotic behavior between inputs and outputs. From the results, we found that the chaotic characteristic of the storage volume which is output is likely a byproduct of the chaotic behavior of the reservoir system itself rather than that of the input data.

  16. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed......., because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail...

  17. ICT-infrastructures for hydrometeorology science and natural disaster societal impact assessment: the DRIHMS project

    Science.gov (United States)

    Parodi, A.; Craig, G. C.; Clematis, A.; Kranzlmueller, D.; Schiffers, M.; Morando, M.; Rebora, N.; Trasforini, E.; D'Agostino, D.; Keil, K.

    2010-09-01

    Hydrometeorological science has made strong progress over the last decade at the European and worldwide level: new modeling tools, post processing methodologies and observational data and corresponding ICT (Information and Communication Technology) technologies are available. Recent European efforts in developing a platform for e-Science, such as EGEE (Enabling Grids for E-sciencE), SEEGRID-SCI (South East Europe GRID e-Infrastructure for regional e-Science), and the German C3-Grid, have demonstrated their abilities to provide an ideal basis for the sharing of complex hydrometeorological data sets and tools. Despite these early initiatives, however, the awareness of the potential of the Grid technology as a catalyst for future hydrometeorological research is still low and both the adoption and the exploitation have astonishingly been slow, not only within individual EC member states, but also on a European scale. With this background in mind and the fact that European ICT-infrastructures are in the progress of transferring to a sustainable and permanent service utility as underlined by the European Grid Initiative (EGI) and the Partnership for Advanced Computing in Europe (PRACE), the Distributed Research Infrastructure for Hydro-Meteorology Study (DRIHMS, co-Founded by the EC under the 7th Framework Programme) project has been initiated. The goal of DRIHMS is the promotion of the Grids in particular and e-Infrastructures in general within the European hydrometeorological research (HMR) community through the diffusion of a Grid platform for e-collaboration in this earth science sector: the idea is to further boost European research excellence and competitiveness in the fields of hydrometeorological research and Grid research by bridging the gaps between these two scientific communities. Furthermore the project is intended to transfer the results to areas beyond the strict hydrometeorology science as a support for the assessment of the effects of extreme

  18. Modelling the effect of land use change on hydrological model ...

    African Journals Online (AJOL)

    Modelling the effect of land use change on hydrological model parameters via linearized calibration method in the upstream of Huaihe River Basin, China. ... is presented, based on the analysis of the problems of the objective function of the ...

  19. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

    Directory of Open Access Journals (Sweden)

    Laura Alfonsina Chang-Martínez

    2015-09-01

    Full Text Available Spatially-explicit land cover land use change (LCLUC models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

  20. Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

    Science.gov (United States)

    Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

    2017-12-01

    Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land grab. Results suggest that the land grab has impacted microclimate parameters in a significant way via direct and indirect impacts on land-atmosphere interactions

  1. Impact of spatio-temporal scale of adjustment on variational assimilation of hydrologic and hydrometeorological data in operational distributed hydrologic models

    Science.gov (United States)

    Lee, H.; Seo, D.; McKee, P.; Corby, R.

    2009-12-01

    One of the large challenges in data assimilation (DA) into distributed hydrologic models is to reduce the large degrees of freedom involved in the inverse problem to avoid overfitting. To assess the sensitivity of the performance of DA to the dimensionality of the inverse problem, we design and carry out real-world experiments in which the control vector in variational DA (VAR) is solved at different scales in space and time, e.g., lumped, semi-distributed, and fully-distributed in space, and hourly, 6 hourly, etc., in time. The size of the control vector is related to the degrees of freedom in the inverse problem. For the assessment, we use the prototype 4-dimenational variational data assimilator (4DVAR) that assimilates streamflow, precipitation and potential evaporation data into the NWS Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM). In this talk, we present the initial results for a number of basins in Oklahoma and Texas.

  2. SET UP OF THE NEW AUTOMATIC HYDROMETEOROLOGICAL NETWORK IN HUNGARY

    Directory of Open Access Journals (Sweden)

    J. NAGy

    2013-03-01

    Full Text Available The Hungarian Meteorological Service (OMSZ and General Directorate of Water Management (OVF in Hungary run conventional precipitation measurement networks consisting of at least 1000 stations. OMSZ automated its synoptic and climatological network in 90’s and now more than 100 automatic stations give data every 1-10 minutes via GPRS channel. In 2007 the experts from both institutions determined the requirements of a common network. The predecessor in title of OVF is general Directorate for Water and Environment gave a project proposal in 2008 for establishment of a new hydrometeorological network based on common aims for meteorology and hydrology. The new hydrometeorological network was set up in 2012 financed by KEOP project. This network has got 141 weighing precipitation gauges, 118 temperature - humidity sensors and 25 soil moisture and soil temperature instruments. Near by Tisza-Lake two wind sensors have been installed. The network is operated by OMSZ and OVF together. OVF and its institutions maintain the stations itself and support the electricity. OMSZ operates data collection and transmission, maintaines and calibrates the sensors. Using precipitation data of enhanced network the radar precipitation field quality may be more precise, which are input of run-off model. Thereby the time allowance may be increased in flood-control events. Based on soil moisture and temperature water balance in soil may be modelled and forecast can be produced in different conditions. It is very important task in drought and inland water conditions. Considering OMSZ investment project in which new Doppler dual polarisation radar and 14 disdrometers will be installed, the precipitation estimation may be improved since 2015.

  3. Land administration domain model is an ISO standard now

    NARCIS (Netherlands)

    Lemmen, Christiaan; van Oosterom, Peter; Uitermark, Harry; de Zeeuw, Kees

    2013-01-01

    A group of land administration professionals initiated the development of a data model that facilitates the quick and efficient set-up of land registrations. Just like social issues benefit from proper land administration, land administration systems themselves benefit from proper data standards. In

  4. Effects of land markets and land management on ecosystem function: A framework for modelling exurban land-change

    NARCIS (Netherlands)

    Robinson, D.T.; Sun, S.; Hutchins, M.; Riolo, R.; Brown, D.G.; Parker, D.C.; Filatova, Tatiana; Currie, W.S.; Kiger, S.

    2013-01-01

    This paper presents the conceptual design and application of a new land-change modelling framework that represents geographical, sociological, economic, and ecological aspects of a land system. The framework provides an overarching design that can be extended into specific model implementations to

  5. Evaluation of historical land cover, land use, and land-use change emissions in the GCAM integrated assessment model

    Science.gov (United States)

    Calvin, K. V.; Wise, M.; Kyle, P.; Janetos, A. C.; Zhou, Y.

    2012-12-01

    Integrated Assessment Models (IAMs) are often used as science-based decision-support tools for evaluating the consequences of climate and energy policies, and their use in this framework is likely to increase in the future. However, quantitative evaluation of these models has been somewhat limited for a variety of reasons, including data availability, data quality, and the inherent challenges in projections of societal values and decision-making. In this analysis, we identify and confront methodological challenges involved in evaluating the agriculture and land use component of the Global Change Assessment Model (GCAM). GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. GCAM then calculates both emissions from land-use practices, and long-term changes in carbon stocks in different land uses, thus providing simulation information that can be compared to observed historical data. In this work, we compare GCAM results, both in recent historic and future time periods, to historical data sets. We focus on land use, land cover, land-use change emissions, and albedo.

  6. Modelling past land use using archaeological and pollen data

    Science.gov (United States)

    Pirzamanbein, Behnaz; Lindström, johan; Poska, Anneli; Gaillard-Lemdahl, Marie-José

    2016-04-01

    Accurate maps of past land use are necessary for studying the impact of anthropogenic land-cover changes on climate and biodiversity. We develop a Bayesian hierarchical model to reconstruct the land use using Gaussian Markov random fields. The model uses two observations sets: 1) archaeological data, representing human settlements, urbanization and agricultural findings; and 2) pollen-based land estimates of the three land-cover types Coniferous forest, Broadleaved forest and Unforested/Open land. The pollen based estimates are obtained from the REVEALS model, based on pollen counts from lakes and bogs. Our developed model uses the sparse pollen-based estimations to reconstruct the spatial continuous cover of three land cover types. Using the open-land component and the archaeological data, the extent of land-use is reconstructed. The model is applied on three time periods - centred around 1900 CE, 1000 and, 4000 BCE over Sweden for which both pollen-based estimates and archaeological data are available. To estimate the model parameters and land use, a block updated Markov chain Monte Carlo (MCMC) algorithm is applied. Using the MCMC posterior samples uncertainties in land-use predictions are computed. Due to lack of good historic land use data, model results are evaluated by cross-validation. Keywords. Spatial reconstruction, Gaussian Markov random field, Fossil pollen records, Archaeological data, Human land-use, Prediction uncertainty

  7. A new MRI land surface model HAL

    Science.gov (United States)

    Hosaka, M.

    2011-12-01

    A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

  8. Modeling Land-Use Decision Behavior with Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Inge Aalders

    2008-06-01

    Full Text Available The ability to incorporate and manage the different drivers of land-use change in a modeling process is one of the key challenges because they are complex and are both quantitative and qualitative in nature. This paper uses Bayesian belief networks (BBN to incorporate characteristics of land managers in the modeling process and to enhance our understanding of land-use change based on the limited and disparate sources of information. One of the two models based on spatial data represented land managers in the form of a quantitative variable, the area of individual holdings, whereas the other model included qualitative data from a survey of land managers. Random samples from the spatial data provided evidence of the relationship between the different variables, which I used to develop the BBN structure. The model was tested for four different posterior probability distributions, and results showed that the trained and learned models are better at predicting land use than the uniform and random models. The inference from the model demonstrated the constraints that biophysical characteristics impose on land managers; for older land managers without heirs, there is a higher probability of the land use being arable agriculture. The results show the benefits of incorporating a more complex notion of land managers in land-use models, and of using different empirical data sources in the modeling process. Future research should focus on incorporating more complex social processes into the modeling structure, as well as incorporating spatio-temporal dynamics in a BBN.

  9. Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

    Directory of Open Access Journals (Sweden)

    J.-P. Vidal

    2010-03-01

    Full Text Available Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc. on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI – and multiscale hydrological droughts, through the Standardized Flow Index (SFI. Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow. Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990 to short hot and dry periods (2003. Results show that the ranking of drought events depends highly

  10. Radiological assessments of land disposal options: recent model developments

    International Nuclear Information System (INIS)

    Fearn, H.S.; Pinner, A.V.; Hemming, C.R.

    1984-10-01

    This report describes progress in the development of methodologies and models for assessing the radiological impact of the disposal of low and intermediate level wastes by (i) shallow land burial in simple trenches (land 1), (ii) shallow land burial in engineered facilities (land 2), and (iii) emplacement in mined repositories or existing cavities (land 3/4). In particular the report describes wasteform leaching models, for unconditioned and cemented waste, the role of engineered barriers of a shallow land burial facility in reducing the magnitude of doses arising from groundwater contact and a detailed consideration of the interactions between radioactive carbon and various media. (author)

  11. Forecasting summertime surface temperature and precipitation in the Mexico City metropolitan area: sensitivity of the WRF model to land cover changes

    Science.gov (United States)

    López-Bravo, Clemente; Caetano, Ernesto; Magaña, Víctor

    2018-02-01

    Changes in the frequency and intensity of severe hydrometeorological events in recent decades in the Mexico City Metropolitan Area have motivated the development of weather warning systems. The weather forecasting system for this region was evaluated in sensitivity studies using the Weather Research and Forecasting Model (WRF) for July 2014, a summer time month. It was found that changes in the extent of the urban area and associated changes in thermodynamic and dynamic variables have induced local circulations that affect the diurnal cycles of temperature, precipitation, and wind fields. A newly implemented configuration (land cover update and Four-Dimensional Data Assimilation (FDDA)) of the WRF model has improved the adjustment of the precipitation field to the orography. However, errors related to the depiction of convection due to parameterizations and microphysics remains a source of uncertainty in weather forecasting in this region.

  12. Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

    Science.gov (United States)

    Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

    2017-11-01

    Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

  13. Spatial modeling of agricultural land use change at global scale

    Science.gov (United States)

    Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

    2014-11-01

    Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

  14. Impacts of historic and projected land-cover, land-use, and land-management change on carbon and water fluxes: The Land Use Model Intercomparison Project (LUMIP)

    Science.gov (United States)

    Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C.

    2017-12-01

    Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available.

  15. A GIS-based hedonic price model for agricultural land

    Science.gov (United States)

    Demetriou, Demetris

    2015-06-01

    Land consolidation is a very effective land management planning approach that aims towards rural/agricultural sustainable development. Land reallocation which involves land tenure restructuring is the most important, complex and time consuming component of land consolidation. Land reallocation relies on land valuation since its fundamental principle provides that after consolidation, each landowner shall be granted a property of an aggregate value that is approximately the same as the value of the property owned prior to consolidation. Therefore, land value is the crucial factor for the land reallocation process and hence for the success and acceptance of the final land consolidation plan. Land valuation is a process of assigning values to all parcels (and its contents) and it is usually carried out by an ad-hoc committee. However, the process faces some problems such as it is time consuming hence costly, outcomes may present inconsistency since it is carried out manually and empirically without employing systematic analytical tools and in particular spatial analysis tools and techniques such as statistical/mathematical. A solution to these problems can be the employment of mass appraisal land valuation methods using automated valuation models (AVM) based on international standards. In this context, this paper presents a spatial based linear hedonic price model which has been developed and tested in a case study land consolidation area in Cyprus. Results showed that the AVM is capable to produce acceptable in terms of accuracy and reliability land values and to reduce time hence cost required by around 80%.

  16. A predictive pilot model for STOL aircraft landing

    Science.gov (United States)

    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.

  17. The North American Monsoon GPS Hydrometeorological Network 2017: A New Look at an Old Problem

    Science.gov (United States)

    Adams, D. K.

    2017-12-01

    Quantifying moisture recycling and determining water vapor source regions for deep convective precipitation have been problematic, particular in tropical continental regions. More than an academic concern, modeling convective precipitation, from cloud-resolving to global climate models, depends critically on properly representing atmospheric water vapor transport, its vertical distribution, as well as surface latent heat flux contributions. The North American Monsoon region, given its complex topography, proximity to warm oceans, striking vegetation "green up" and oftentimes subtle dynamical forcing is particular challenging in this regard. Recent studies, employing modeling and observational approaches, give a prominent role for moisture recycling in fomenting deep convective precipitation. Likewise, these studies argue for the increased importance of transport from the Gulf of Mexico/Central America and the Atlantic Ocean, relative to the Pacific Ocean/Gulf of California. In this presentation, we critically review these studies which served to motivate the NAM GPS Hydrometeorological Network 2017, detailed here. This bi-national (Mexico-US) 3-month campaign to examine water vapor source regions, and specifically, land-surface water vapor fluxes consists of 10 experimental GPS meteorological sites as well as TLALOCNet and Suominet GPS sites in the Mexican states of Sonora, Chihuahua, Sinaloa, and Baja California and in Arizona and New Mexico. Near Rayón Sonora, inside the larger regional GPSmet array, a 30km eddy covariance flux tower triangular array, with collocated GPSmet, measures continuous energy fluxes and precipitable water vapor. Preliminary results examining the local flux contribution in the triangular array to total precipitable water vapor measured are presented. Further research is then outlined.

  18. Application of hydrometeorological coupled European flood forecasting operational real time system in Yellow River Basin

    Directory of Open Access Journals (Sweden)

    Yi-qi Yan

    2009-12-01

    Full Text Available This study evaluated the application of the European flood forecasting operational real time system (EFFORTS to the Yellow River. An automatic data pre-processing program was developed to provide real-time hydrometeorological data. Various GIS layers were collected and developed to meet the demands of the distributed hydrological model in the EFFORTS. The model parameters were calibrated and validated based on more than ten years of historical hydrometeorological data from the study area. The San-Hua Basin (from the Sanmenxia Reservoir to the Huayuankou Hydrological Station, the most geographically important area of the Yellow River, was chosen as the study area. The analysis indicates that the EFFORTS enhances the work efficiency, extends the flood forecasting lead time, and attains an acceptable level of forecasting accuracy in the San-Hua Basin, with a mean deterministic coefficient at Huayuankou Station, the basin outlet, of 0.90 in calibration and 0.96 in validation. The analysis also shows that the simulation accuracy is better for the southern part than for the northern part of the San-Hua Basin. This implies that, along with the characteristics of the basin and the mechanisms of runoff generation of the hydrological model, the hydrometeorological data play an important role in simulation of hydrological behavior.

  19. Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

    Science.gov (United States)

    Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

    2016-12-01

    Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

  20. Tropical Montane Cloud Forests: Hydrometeorological variability in three neighbouring catchments with different forest cover

    Science.gov (United States)

    Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik

    2017-09-01

    Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response

  1. Empirically derived neighbourhood rules for urban land-use modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2012-01-01

    Land-use modelling and spatial scenarios have gained attention as a means to meet the challenge of reducing uncertainty in spatial planning and decision making. Many of the recent modelling efforts incorporate cellular automata to accomplish spatially explicit land-use-change modelling. Spatial...

  2. Developing land market data for use in a state wide land use and transportation model

    Science.gov (United States)

    1997-10-01

    This working paper describes the process used to develop land market variables : for use by TRANUS in the Transportation and Land Use Model Integration : Program (TLUMIP). One of the key variables developed during this phase of the : project is the m...

  3. Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

    2011-01-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  4. Land surface Verification Toolkit (LVT) - a generalized framework for land surface model evaluation

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J.; Harrison, K.; Liu, Y.; Shaw, M.

    2012-06-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  5. Integrated modelling of anthropogenic land-use and land-cover change on the global scale

    Science.gov (United States)

    Schaldach, R.; Koch, J.; Alcamo, J.

    2009-04-01

    In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information

  6. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

    2012-01-01

    Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  7. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, J. A.; Kumar, S.; Peters-Lidard, C. D.; Harrison, K. W.; Zhou, S.

    2012-12-01

    Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  8. The Czech Hydrometeorological Institute's severe storm nowcasting system

    Science.gov (United States)

    Novak, Petr

    2007-02-01

    To satisfy requirements for operational severe weather monitoring and prediction, the Czech Hydrometeorological Institute (CHMI) has developed a severe storm nowcasting system which uses weather radar data as its primary data source. Previous CHMI studies identified two methods of radar echo prediction, which were then implemented during 2003 into the Czech weather radar network operational weather processor. The applications put into operations were the Continuity Tracking Radar Echoes by Correlation (COTREC) algorithm, and an application that predicts future radar fields using the wind field derived from the geopotential at 700 hPa calculated from a local numerical weather prediction model (ALADIN). To ensure timely delivery of the prediction products to the users, the forecasts are implemented into a web-based viewer (JSMeteoView) that has been developed by the CHMI Radar Department. At present, this viewer is used by all CHMI forecast offices for versatile visualization of radar and other meteorological data (Meteosat, lightning detection, NWP LAM output, SYNOP data) in the Internet/Intranet environment, and the viewer has detailed geographical navigation capabilities.

  9. Pairing FLUXNET sites to validate model representations of land-use/land-cover change

    Science.gov (United States)

    Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

    2018-01-01

    Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

  10. MODELING OF FUTURE LAND COVER LAND USE CHANGE IN NORTH CAROLINA USING MARKOV CHAIN AND CELLULAR AUTOMATA MODEL

    OpenAIRE

    Mohammad Sayemuzzaman; Manoj K. Jha

    2014-01-01

    State wide variant topographic features in North Carolina attract the hydro-climatologist. There is none modeling study found that predict future Land Cover Land Use (LCLU) change for whole North Carolina. In this study, satellite-derived land cover maps of year 1992, 2001 and 2006 of North Carolina were integrated within the framework of the Markov-Cellular Automata (Markov-CA) model which combines the Markov chain and Cellular Automata (CA) techniques. A Multi-Criteria Evaluation (MCE) was ...

  11. Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

    Directory of Open Access Journals (Sweden)

    Iqra Atif

    2018-04-01

    Full Text Available The Upper Indus basin (UIB is characterized by contrasting hydrometeorological behaviors; therefore, it has become pertinent to understand hydrometeorological trends at the sub-watershed level. Many studies have investigated the snow cover and hydrometeorological modeling at basin level but none have reported the spatial variability of trends and their magnitude at a sub-basin level. This study was conducted to analyze the trends in the contrasting hydrological regimes of the snow and glacier-fed river catchments of the Hunza and Astore sub-basins of the UIB. Mann-Kendall and Sen’s slope methods were used to study the main trends and their magnitude using MODIS snow cover information (2001–2015 and hydrometeorological data. The results showed that in the Hunza basin, the river discharge and temperature were significantly (p ≤ 0.05 decreased with a Sen’s slope value of −2.541 m3·s−1·year−1 and −0.034 °C·year−1, respectively, while precipitation data showed a non-significant (p ≥ 0.05 increasing trend with a Sen’s slope value of 0.023 mm·year−1. In the Astore basin, the river discharge and precipitation are increasing significantly (p ≤ 0.05 with a Sen’s slope value of 1.039 m3·s−1·year−1 and 0.192 mm·year−1, respectively. The snow cover analysis results suggest that the Western Himalayas (the Astore basin had a stable trend with a Sen’s slope of 0.07% year−1 and the Central Karakoram region (the Hunza River basin shows a slightly increasing trend with a Sen’s slope of 0.394% year−1. Based on the results of this study it can be concluded that since both sub-basins are influenced by different climatological systems (monsoon and westerly, the results of those studies that treat the Upper Indus basin as one unit in hydrometeorological modeling should be used with caution. Furthermore, it is suggested that similar studies at the sub-basin level of the UIB will help in a better understanding of the

  12. Climate change and land use. Towards the Nexus Land Use model

    International Nuclear Information System (INIS)

    Mazas, C.

    2007-01-01

    The objective of this study is to examine the impacts of arbitrations on land use (choice between urban development, agriculture, infrastructures, forests, free spaces, and so on, which are concurrent and exclusive) on greenhouse gas emissions. The first part highlights the complexity of this issue as land use can both generate important greenhouse gas emissions (through deforestation, methane emission by cattle, nitrogenous fertilizers) and absorb large quantities of CO 2 . The second part analyses and discusses the extent and the reasons of deforestation, commenting the situation in developed countries and in the case of the tropical forest. The third part describes the competition between land uses, reviews existing economical models, and presents the Nexus Land Use model which could be able to integrate agricultural and forestry challenges at the planet scale

  13. Modelling land change: the issue of use and cover in wide-scale applications

    NARCIS (Netherlands)

    Bakker, M.M.; Veldkamp, A.

    2008-01-01

    In this article, the underlying causes for the apparent mismatch between land cover and land use in the context of wide-scale land change modelling are explored. A land use-land cover (LU/LC) ratio is proposed as a relevant landscape characteristic. The one-to-one ratio between land use and land

  14. Implementing land use change models in the developing world

    CSIR Research Space (South Africa)

    Le Roux, Alize

    2013-07-01

    Full Text Available recently adapted land use change models (Dyna-Clue and UrbanSIM) that have been successfully adapted to simulate future land use change policies in the various metro's across South-Africa. The presentation will focus on how these technologies together...

  15. Modeling land development along highway 4 in Southern Thailand

    Directory of Open Access Journals (Sweden)

    Potjamas Chuangchang

    2014-12-01

    Full Text Available This study aims to investigate the change of developed land in three different locations along Highway 4 Road from Phattalung to HatYai. The method involves creating a digitized grid of geographical coordinates covering the study area. The land-use codes and plot identifiers were recorded in database tables indexed by grid coordinates. Logistic regression of land development adjusted for spatial correlation was used to model its change over a 9-year period using land-use at the previous survey combined with location as a determinant. The results show increasing average percentages of developed land (3% in 2000 and 5% in 2009. Land development occurred mostly in the northern location along the Pattalung to HatYai road.

  16. Geographical information modelling for land resource survey

    NARCIS (Netherlands)

    Bruin, de S.

    2000-01-01

    The increasing popularity of geographical information systems (GIS) has at least three major implications for land resources survey. Firstly, GIS allows alternative and richer representation of spatial phenomena than is possible with the traditional paper map. Secondly, digital technology has

  17. Hydrometeorological extremes at the Veselí nad Moravou estate (Czech Republic) in the period 1794-1850 derived from documentary evidence of the economic character

    Science.gov (United States)

    Chromá, Kateřina

    2010-05-01

    Hydrometeorological extremes influenced always human activities (agriculture, forestry, water management) and caused losses of human lives and great material damage. Systematic meteorological and hydrological observations in the Czech Lands (recent Czech Republic) started generally in the latter half of the 19th century. In order to create long-term series of hydrometeorological extremes, it is necessary to search for other sources of information for their study before 1850. Such direct and indirect information about hydrometeorological extremes is included in documentary evidence (e.g. chronicles, memoirs, diaries, early visual weather observations, newspapers, economic sources etc.). Documentary evidence of economic character belongs to the most important sources, especially documents related to taxation records. Damage to agricultural crops on the fields or damage to hay on meadows due to the hydrological and meteorological phenomena has been a good reason for the abatement of tax duty. Based on the official correspondence of the estate of Veselí nad Moravou (southern Moravia), archival information about taxation from the Moravian Land Archives in Brno was excerpted. Based on it, 46 hydrometeorological extremes which occurred between the years 1794 and 1850 were selected and further analysed. Because of fields and meadows of the above estate were located along the Morava River, reports of damage due to floods were the most frequent, followed by damage due to torrential rains and hailstorms.

  18. Statistical variability of hydro-meteorological variables as indicators ...

    African Journals Online (AJOL)

    Statistical variability of hydro-meteorological variables as indicators of climate change in north-east Sokoto-Rima basin, Nigeria. ... water resources development including water supply project, agriculture and tourism in the study area. Key word: Climate change, Climatic variability, Actual evapotranspiration, Global warming ...

  19. An Uncertain Programming Model for Land Use Structure Optimization to Promote Effectiveness of Land Use Planning

    Institute of Scientific and Technical Information of China (English)

    LI Xin; MA Xiaodong

    2017-01-01

    Land use structure optimization (LUSO) is an important issue for land use planning.In order for land use planning to have reasonable flexibility,uncertain optimization should be applied for LUSO.In this paper,the researcher first expounded the uncertainties of LUSO.Based on this,an interval programming model was developed,of which interval variables were to hold land use uncertainties.To solve the model,a heuristics based on Genetic Algorithm was designed according to Pareto Optimum principle with a confidence interval under given significance level to represent LUSO result.Proposed method was applied to a real case of Yangzhou,an eastern city in China.The following conclusions were reached.1) Different forms of uncertainties ranged from certainty to indeterminacy lay in the five steps of LUSO,indicating necessary need of comprehensive approach to quantify them.2) With regards to trade-offs of conflicted objectives and preferences to uncertainties,our proposed model displayed good ability of making planning decision process transparent,therefore providing an effective tool for flexible land use planning compiling.3) Under uncertain conditions,land use planning effectiveness can be primarily enhanced by flexible management with reserved space to percept and hold uncertainties in advance.

  20. Simulating Land-Use Change using an Agent-Based Land Transaction Model

    Science.gov (United States)

    Bakker, M. M.; van Dijk, J.; Alam, S. J.

    2013-12-01

    In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are

  1. Comparison of Predictive Modeling Methods of Aircraft Landing Speed

    Science.gov (United States)

    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.

  2. Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

    Science.gov (United States)

    DeChant, C. M.; Moradkhani, H.

    2014-12-01

    Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

  3. Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

    Science.gov (United States)

    Guo, Danlu; Westra, Seth; Maier, Holger R.

    2017-11-01

    Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific

  4. Land

    NARCIS (Netherlands)

    C.A. Hunsberger (Carol); Tom P. Evans

    2012-01-01

    textabstractPressure on land resources has increased during recent years despite international goals to improve their management. The fourth Global Environment Outlook (UNEP 2007) highlighted the unprecedented land-use changes created by a burgeoning population, economic development and

  5. Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

    Science.gov (United States)

    van Westen, Cees

    2013-04-01

    In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and

  6. High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

    Science.gov (United States)

    Shin, S.; Pokhrel, Y. N.

    2016-12-01

    Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

  7. Modeled impact of anthropogenic land cover change on climate

    Science.gov (United States)

    Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

    2007-01-01

    Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

  8. Possibilities of Land Administration Domain Model (ladm) Implementation in Nigeria

    Science.gov (United States)

    Babalola, S. O.; Rahman, A. Abdul; Choon, L. T.; Van Oosterom, P. J. M.

    2015-10-01

    LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a land administration system that allows a shared explanation of different formal customary or informal tenures. The standard provides the basis for national and regional profiles and enables the combination of land management information from different sources in a coherent manner. Given this, this paper started with the description of land and land administration in Nigeria. The pre-colonial, colonial and post-colonial era with organization structure was discussed. This discussion is important to present an understanding of the background of any improvement needed for the LADM implementation in Nigeria. The LADM, ISO 19152 and the packages of LADM was discussed, and the comparison of the different aspects of each package and classes were made with Nigerian land administration and the cadastral system. In the comparison made, it was discovered that the concept is similar to LADM packages in Nigerian land administration. Although, the terminology may not be the same in all cases. Having studied conceptualization and the application of LADM, as a model that has essential information associated with components of the land administration. Including those on the land, over water as well as elements above and below the surface of the earth and discovered that the standard is suitable for the country. The model can, therefore, be adopted into Nigerian land administration system by mapping in some of the concepts of LADM.

  9. Data model for the collaboration between land administration systems and agricultural land parcel identification systems.

    Science.gov (United States)

    Inan, Halil Ibrahim; Sagris, Valentina; Devos, Wim; Milenov, Pavel; van Oosterom, Peter; Zevenbergen, Jaap

    2010-12-01

    The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included. Copyright © 2010 Elsevier Ltd. All rights reserved.

  10. Co-evolution of transportation and land use : modeling historical dependencies in land use and transportation decision making.

    Science.gov (United States)

    2009-11-01

    The interaction between land use and transportation has long been the central issue in urban and regional planning. Models of such : interactions provide vital information to support many public policy decisions, such as land supply, infrastructure p...

  11. Polarimetric SAR interferometry applied to land ice: modeling

    DEFF Research Database (Denmark)

    Dall, Jørgen; Papathanassiou, Konstantinos; Skriver, Henning

    2004-01-01

    This paper introduces a few simple scattering models intended for the application of polarimetric SAR interfer-ometry to land ice. The principal aim is to eliminate the penetration bias hampering ice sheet elevation maps generated with single-channel SAR interferometry. The polarimetric coherent...... scattering models are similar to the oriented-volume model and the random-volume-over-ground model used in vegetation studies, but the ice models are adapted to the different geometry of land ice. Also, due to compaction, land ice is not uniform; a fact that must be taken into account for large penetration...... depths. The validity of the scattering models is examined using L-band polarimetric interferometric SAR data acquired with the EMISAR system over an ice cap located in the percolation zone of the Greenland ice sheet. Radar reflectors were deployed on the ice surface prior to the data acquisition in order...

  12. Land use allocation model considering climate change impact

    Science.gov (United States)

    Lee, D. K.; Yoon, E. J.; Song, Y. I.

    2017-12-01

    In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

  13. Family archives as a source of information about past hydrometeorological extremes in Southern Moravia (Czech Republic)

    Science.gov (United States)

    Chromá, Kateřina

    2014-05-01

    Meteorological and hydrological extremes (hydrometeorological extremes - HMEs) cause great material damage or even loss of human lives in the present time, as well as it was in the past. For the study of their temporal and spatial variability in periods with only natural forcing factors in comparison with those combining also anthropogenic effects it is essential to have the longest possible series of HMEs. In the Czech Lands (recently the Czech Republic), systematic meteorological and hydrological observations started generally in the latter half of the 19th century. Therefore, in order to create long-term series of such extremes, it is necessary to search for other sources of information. There exist different types of documentary evidence used in historical climatology and hydrology, represented by various sources such as annals, chronicles, diaries, private letters, newspapers etc. Besides them, institutional documentary evidence (of economic and administrative character) has particular importance (e.g. taxation records). Documents in family archives represent further promising source of data related to HMEs. The documents kept by the most important lord families in Moravia (e.g. Liechtensteins, Dietrichsteins) are located in Moravian Land Archives in Brno. Besides data about family members, industrial and agricultural business, military questions, travelling and social events, they contain direct or indirect information about HMEs. It concerns descriptions of catastrophic phenomena on the particular demesne (mainly with respect to damage) as well as correspondence related to tax reductions (i.e. they can overlap with taxation records of particular estates). This contribution shows the potential of family archives as a source of information about HMEs, up to now only rarely used, which may extend our knowledge about them. Several examples of such documents are presented. The study is a part of the research project "Hydrometeorological extremes in Southern

  14. EVALUATION OF LAND USE/LAND COVER DATASETS FOR URBAN WATERSHED MODELING

    International Nuclear Information System (INIS)

    S.J. BURIAN; M.J. BROWN; T.N. MCPHERSON

    2001-01-01

    Land use/land cover (LULC) data are a vital component for nonpoint source pollution modeling. Most watershed hydrology and pollutant loading models use, in some capacity, LULC information to generate runoff and pollutant loading estimates. Simple equation methods predict runoff and pollutant loads using runoff coefficients or pollutant export coefficients that are often correlated to LULC type. Complex models use input variables and parameters to represent watershed characteristics and pollutant buildup and washoff rates as a function of LULC type. Whether using simple or complex models an accurate LULC dataset with an appropriate spatial resolution and level of detail is paramount for reliable predictions. The study presented in this paper compared and evaluated several LULC dataset sources for application in urban environmental modeling. The commonly used USGS LULC datasets have coarser spatial resolution and lower levels of classification than other LULC datasets. In addition, the USGS datasets do not accurately represent the land use in areas that have undergone significant land use change during the past two decades. We performed a watershed modeling analysis of three urban catchments in Los Angeles, California, USA to investigate the relative difference in average annual runoff volumes and total suspended solids (TSS) loads when using the USGS LULC dataset versus using a more detailed and current LULC dataset. When the two LULC datasets were aggregated to the same land use categories, the relative differences in predicted average annual runoff volumes and TSS loads from the three catchments were 8 to 14% and 13 to 40%, respectively. The relative differences did not have a predictable relationship with catchment size

  15. Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

    Science.gov (United States)

    Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

    2014-01-01

    Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

  16. lands

    Directory of Open Access Journals (Sweden)

    A.T. O'Geen

    2015-04-01

    Full Text Available Groundwater pumping chronically exceeds natural recharge in many agricultural regions in California. A common method of recharging groundwater — when surface water is available — is to deliberately flood an open area, allowing water to percolate into an aquifer. However, open land suitable for this type of recharge is scarce. Flooding agricultural land during fallow or dormant periods has the potential to increase groundwater recharge substantially, but this approach has not been well studied. Using data on soils, topography and crop type, we developed a spatially explicit index of the suitability for groundwater recharge of land in all agricultural regions in California. We identified 3.6 million acres of agricultural land statewide as having Excellent or Good potential for groundwater recharge. The index provides preliminary guidance about the locations where groundwater recharge on agricultural land is likely to be feasible. A variety of institutional, infrastructure and other issues must also be addressed before this practice can be implemented widely.

  17. Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

    OpenAIRE

    Baysal, Gülendam

    2013-01-01

    Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies. This research was conducted to analyze the land use and land cover changes and to model the changes for the case study area Malatya, Turkey. The first step of the study was acquisition of multi temporal data in order to detect the changes over the time. For this purpose satellite images (Landsat 1990-2000-2010) have been used. In order to acquire data from satel...

  18. Hydrometeorological Database (HMDB) for Practical Research in Ecology

    OpenAIRE

    Novakovskiy, A; Elsakov, V

    2014-01-01

    The regional HydroMeteorological DataBase (HMDB) was designed for easy access to climate data via the Internet. It contains data on various climatic parameters (temperature, precipitation, pressure, humidity, and wind strength and direction) from 190 meteorological stations in Russia and bordering countries for a period of instrumental observations of over 100 years. Open sources were used to ingest data into HMDB. An analytical block was also developed to perform the most common statistical ...

  19. Modelling animal waste pathogen transport from agricultural land to streams

    International Nuclear Information System (INIS)

    Pandey, Pramod K; Soupir, Michelle L; Ikenberry, Charles

    2014-01-01

    The transport of animal waste pathogens from crop land to streams can potentially elevate pathogen levels in stream water. Applying animal manure into crop land as fertilizers is a common practice in developing as well as in developed countries. Manure application into the crop land, however, can cause potential human health. To control pathogen levels in ambient water bodies such as streams, improving our understanding of pathogen transport at farm scale as well as at watershed scale is required. To understand the impacts of crop land receiving animal waste as fertilizers on stream's pathogen levels, here we investigate pathogen indicator transport at watershed scale. We exploited watershed scale hydrological model to estimate the transport of pathogens from the crop land to streams. Pathogen indicator levels (i.e., E. coli levels) in the stream water were predicted. With certain assumptions, model results are reasonable. This study can be used as guidelines for developing the models for calculating the impacts of crop land's animal manure on stream water

  20. Enhancing the representation of subgrid land surface characteristics in land surface models

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2013-09-01

    Full Text Available Land surface heterogeneity has long been recognized as important to represent in the land surface models. In most existing land surface models, the spatial variability of surface cover is represented as subgrid composition of multiple surface cover types, although subgrid topography also has major controls on surface processes. In this study, we developed a new subgrid classification method (SGC that accounts for variability of both topography and vegetation cover. Each model grid cell was represented with a variable number of elevation classes and each elevation class was further described by a variable number of vegetation types optimized for each model grid given a predetermined total number of land response units (LRUs. The subgrid structure of the Community Land Model (CLM was used to illustrate the newly developed method in this study. Although the new method increases the computational burden in the model simulation compared to the CLM subgrid vegetation representation, it greatly reduced the variations of elevation within each subgrid class and is able to explain at least 80% of the total subgrid plant functional types (PFTs. The new method was also evaluated against two other subgrid methods (SGC1 and SGC2 that assigned fixed numbers of elevation and vegetation classes for each model grid (SGC1: M elevation bands–N PFTs method; SGC2: N PFTs–M elevation bands method. Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0°and 2.0° with three maximum-allowed total number of LRUs (i.e., NLRU of 24, 18 and 12 over North America (NA, the new method yielded more computationally efficient subgrid representation compared to SGC1 and SGC2, particularly at coarser model resolutions and moderate computational intensity (NLRU = 18. It also explained the most PFTs and elevation variability that is more homogeneously distributed spatially. The SGC method will be implemented in CLM over the NA continent to assess its impacts on

  1. Supporting Hydrometeorological Research and Applications with Global Precipitation Measurement (GPM) Products and Services

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; MacRitchie, K.; Greene, M.; Kempler, S.

    2016-01-01

    Precipitation is an important dataset in hydrometeorological research and applications such as flood modeling, drought monitoring, etc. On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data. The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). GPM products currently available include the following:1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products2. Goddard Profiling Algorithm (GPROF) GMI and partner products (Level-2 and Level-3)3. GPM dual-frequency precipitation radar and their combined products (Level-2 and Level-3)4. Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final run)GPM data can be accessed through a number of data services (e.g., Simple Subset Wizard, OPeNDAP, WMS, WCS, ftp, etc.). A newly released Unified User Interface or UUI is a single interface to provide users seamless access to data, information and services. For example, a search for precipitation products will not only return TRMM and GPM products, but also other global precipitation products such as MERRA (Modern Era Retrospective-Analysis for Research and Applications), GLDAS (Global Land Data Assimilation Systems), etc.New features and capabilities have been recently added in GIOVANNI to allow exploring and inter-comparing GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) half-hourly and monthly precipitation

  2. TLALOCNet continuous GPS-Met Array in Mexico supporting the 2017 NAM GPS Hydrometeorological Network.

    Science.gov (United States)

    Cabral-Cano, E.; Salazar-Tlaczani, L.; Adams, D. K.; Vivoni, E. R.; Grutter, M.; Serra, Y. L.; DeMets, C.; Galetzka, J.; Feaux, K.; Mattioli, G. S.; Miller, M. M.

    2017-12-01

    TLALOCNet is a network of continuous GPS and meteorology stations in Mexico to study atmospheric and solid earth processes. This recently completed network spans most of Mexico with a strong coverage emphasis on southern and western Mexico. This network, funded by NSF, CONACyT and UNAM, recently built 40 cGPS-Met sites to EarthScope Plate Boundary Observatory standards and upgraded 25 additional GPS stations. TLALOCNet provides open and freely available raw GPS data, and high frequency surface meteorology measurements, and time series of daily positions. This is accomplished through the development of the TLALOCNet data center (http://tlalocnet.udg.mx) that serves as a collection and distribution point. This data center is based on UNAVCO's Dataworks-GSAC software and also works as part of UNAVCO's seamless archive for discovery, sharing, and access to GPS data. The TLALOCNet data center also contains contributed data from several regional GPS networks in Mexico for a total of 100+ stations. By using the same protocols and structure as the UNAVCO and other COCONet regional data centers, the scientific community has the capability of accessing data from the largest Mexican GPS network. This archive provides a fully queryable and scriptable GPS and Meteorological data retrieval point. In addition, real-time 1Hz streams from selected TLALOCNet stations are available in BINEX, RTCM 2.3 and RTCM 3.1 formats via the Networked Transport of RTCM via Internet Protocol (NTRIP) for real-time seismic and weather forecasting applications. TLALOCNet served as a GPS-Met backbone for the binational Mexico-US North American Monsoon GPS Hydrometeorological Network 2017 campaign experiment. This innovative experiment attempts to address water vapor source regions and land-surface water vapor flux contributions to precipitation (i.e., moisture recycling) during the 2017 North American Monsoon in Baja California, Sonora, Chihuahua, and Arizona. Models suggest that moisture recycling is

  3. Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France

    Directory of Open Access Journals (Sweden)

    J. Etchanchu

    2017-11-01

    Full Text Available Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA land surface model included in the EXternalized SURface (SURFEX modeling platform. The study focuses on the effect of the leaf area index (LAI spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m. The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km. An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE. Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE in the simulated evapotranspiration. This

  4. Performance comparison of land change modeling techniques for land use projection of arid watersheds

    Directory of Open Access Journals (Sweden)

    S.M. Tajbakhsh

    2018-07-01

    Full Text Available The change of land use/land cover has been known as an imperative force in environmental alteration, especially in arid and semi-arid areas. This research was mainly aimed to assess the validity of two major types of land change modeling techniques via a three dimensional approach in Birjand urban watershed located in an arid climatic region of Iran. Thus, a Markovian approach based on two suitability and transition potential mappers, i.e. fuzzy analytic hierarchy process and artificial neural network-multi layer perceptron was used to simulate land use map. Validation metrics, quantity disagreement, allocation disagreement and figure of merit in a three-dimensional space were used to perform model validation. Utilizing the fuzzy-analytic hierarchy processsimulation of total landscape in the target point 2015, quantity error, the figure of merit and allocation error were 2%, 18.5% and 8%, respectively. However, Artificial neural network-multi layer perceptron simulation led to a marginal improvement in figure of merit, i.e. 3.25%.

  5. Land-surface modelling in hydrological perspective ? a review

    OpenAIRE

    Overgaard , J.; Rosbjerg , D.; Butts , M. B.

    2006-01-01

    International audience; The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opport...

  6. Multimedia Modeling System Response to Regional Land Management Change

    Science.gov (United States)

    Cooter, E. J.

    2015-12-01

    A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of Research and Development. It is populated with linked or fully coupled models that address nutrient research questions such as, "How might future policy, climate or land cover change in the Mississippi River Basin affect Nitrogen and Phosphorous loadings to the Gulf of Mexico" or, "What are the management implications of regional-scale land management changes for the sustainability of air, land and water quality?" This second question requires explicit consideration of economic (e.g. sector prices) and societal (e.g. land management) factors. Metrics that illustrate biosphere-atmosphere interactions such as atmospheric PM2.5 concentrations, atmospheric N loading to surface water, soil organic N and N percolation to groundwater are calculated. An example application has been completed that is driven by a coupled agricultural and energy sector model scenario. The economic scenario assumes that by 2022 there is: 1) no detectable change in weather patterns relative to 2002; 2) a concentration of stover processing facilities in the Upper Midwest; 3) increasing offshore Pacific and Atlantic marine transportation; and 4) increasing corn, soybean and wheat production that meets future demand for food, feed and energy feedstocks. This production goal is reached without adding or removing agricultural land area whose extent is defined by the National Land Cover Dataset (NLCD) 2002v2011 classes 81 and 82. This goal does require, however, crop shifts and agricultural management changes. The multi-media system response over our U.S. 12km rectangular grid resolution analysis suggests that there are regions of potential environmental and health costs, as well as large areas that could experience unanticipated environmental and health

  7. Analyzing historical land use changes using a Historical Land Use Reconstruction Model: a case study in Zhenlai County, northeastern China

    Science.gov (United States)

    Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui; Xing, Xiaoshi; de Sherbinin, Alex

    2017-01-01

    Historical land use information is essential to understanding the impact of anthropogenic modification of land use/cover on the temporal dynamics of environmental and ecological issues. However, due to a lack of spatial explicitness, complete thematic details and the conversion types for historical land use changes, the majority of historical land use reconstructions do not sufficiently meet the requirements for an adequate model. Considering these shortcomings, we explored the possibility of constructing a spatially-explicit modeling framework (HLURM: Historical Land Use Reconstruction Model). Then a three-map comparison method was adopted to validate the projected reconstruction map. The reconstruction suggested that the HLURM model performed well in the spatial reconstruction of various land-use categories, and had a higher figure of merit (48.19%) than models used in other case studies. The largest land use/cover type in the study area was determined to be grassland, followed by arable land and wetland. Using the three-map comparison, we noticed that the major discrepancies in land use changes among the three maps were as a result of inconsistencies in the classification of land-use categories during the study period, rather than as a result of the simulation model. PMID:28134342

  8. Nutrient cycle benchmarks for earth system land model

    Science.gov (United States)

    Zhu, Q.; Riley, W. J.; Tang, J.; Zhao, L.

    2017-12-01

    Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.

  9. Highlights of advances in the field of hydrometeorological research brought about by the DRIHM project

    Science.gov (United States)

    Caumont, Olivier; Hally, Alan; Garrote, Luis; Richard, Évelyne; Weerts, Albrecht; Delogu, Fabio; Fiori, Elisabetta; Rebora, Nicola; Parodi, Antonio; Mihalović, Ana; Ivković, Marija; Dekić, Ljiljana; van Verseveld, Willem; Nuissier, Olivier; Ducrocq, Véronique; D'Agostino, Daniele; Galizia, Antonella; Danovaro, Emanuele; Clematis, Andrea

    2015-04-01

    The FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, http://www.drihm.eu, 2011-2015) project intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in Hydro-Meteorology Research (HMR). As the project comes to its end, this presentation will summarize the HMR results that have been obtained in the framework of DRIHM. The vision shaped and implemented in the framework of the DRIHM project enables the production and interpretation of numerous, complex compositions of hydrometeorological simulations of flood events from rainfall, either simulated or modelled, down to discharge. Each element of a composition is drawn from a set of various state-of-the-art models. Atmospheric simulations providing high-resolution rainfall forecasts involve different global and limited-area convection-resolving models, the former being used as boundary conditions for the latter. Some of these models can be run as ensembles, i.e. with perturbed boundary conditions, initial conditions and/or physics, thus sampling the probability density function of rainfall forecasts. In addition, a stochastic downscaling algorithm can be used to create high-resolution rainfall ensemble forecasts from deterministic lower-resolution forecasts. All these rainfall forecasts may be used as input to various rainfall-discharge hydrological models that compute the resulting stream flows for catchments of interest. In some hydrological simulations, physical parameters are perturbed to take into account model errors. As a result, six different kinds of rainfall data (either deterministic or probabilistic) can currently be compared with each other and combined with three different hydrological model engines running either in deterministic or probabilistic mode. HMR topics which are allowed or facilitated by such unprecedented sets of hydrometerological forecasts

  10. Uncertainty analysis of hydro-meteorological forecasts

    OpenAIRE

    Grythe, Karl Kristian; Gao, Yukun

    2010-01-01

    Masteroppgave i informasjons- og kommunikasjonsteknologi 2010 – Universitetet i Agder, Grimstad Meteorological and hydrological forecasts are very important to human’s life which concerns agriculture, industry, transport, etc. The Nordic hydropower industry use and develop hydrological forecasting models to make predictions of rivers steam flow. The quantity of incoming stream flow is important to the electricity production because excessive water in reservoir will cause flood ...

  11. Modeling socioeconomic and ecologic aspects of land-use change

    International Nuclear Information System (INIS)

    Dale, V.H.; Pedlowski, M.A.; O'Neill, R.V.; Southworth, F.

    1992-01-01

    Land use change is one of the major factors affecting global environmental conditions. Prevalent types of land-use change include replacing forests with agriculture, mines or ranches; forest degradation from collection of firewood; and forest logging. A global effect of wide-scale deforestation is an increase in atmospheric carbon dioxide concentration, which may affect climate. Regional effects include loss of biodiversity and disruption of hydrologic regimes. Local effects include soil erosion, siltation and decreases in soil fertility, loss of extractive reserves, and disruption of indigenous people. Modeling land use change requires combining socioeconomic and ecological factors because socioeconomic forces frequently initiate land-use change and are affected by the subsequent ecological degradation. This paper describes a modeling system that integrates submodels of human colonization and impacts to estimate patterns and rates of deforestation under different immigration and land use scenarios. Immigration which follows road building or paving is a major factor in the rapid deforestation of previously inaccessible areas. Roads facilitate colonization, allow access for large machines, and provide transportation routes for mort of raw materials and produce

  12. Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies

    Data.gov (United States)

    National Aeronautics and Space Administration — The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces...

  13. A Stochastic Model for the Landing Dispersion of Hazard Detection and Avoidance Capable Flight Systems

    Science.gov (United States)

    Witte, L.

    2014-06-01

    To support landing site assessments for HDA-capable flight systems and to facilitate trade studies between the potential HDA architectures versus the yielded probability of safe landing a stochastic landing dispersion model has been developed.

  14. Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

    Science.gov (United States)

    WANG, D.; Wang, Y.; Zeng, X.

    2017-12-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

  15. Land

    CSIR Research Space (South Africa)

    Audouin, M

    2007-01-01

    Full Text Available the factors contributing to desertification and practical measures necessary to combat desertification and mitigate the effect of drought. The priority issues reported on in this chapter are soil and veld degradation, and the loss of land for agricultural use....

  16. Role of land state in a high resolution mesoscale model

    Indian Academy of Sciences (India)

    ... Proceedings – Mathematical Sciences · Resonance – Journal of Science ... Land surface characteristics; high resolution mesoscale model; Uttarakhand ... to predict realistic location, timing, amount,intensity and distribution of rainfall ... region embedded within two low pressure centers over Arabian Seaand Bay of Bengal.

  17. Possibilities of Land Administration Domain Model (LADM) implementation in Nigeria

    NARCIS (Netherlands)

    Babalola, S.O.; Rahman, A.A.; Choon, L.T.; Van Oosterom, P.J.M.

    2015-01-01

    LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a

  18. Modelling the Landing of a Plane in a Calculus Lab

    Science.gov (United States)

    Morante, Antonio; Vallejo, Jose A.

    2012-01-01

    We exhibit a simple model of a plane landing that involves only basic concepts of differential calculus, so it is suitable for a first-year calculus lab. We use the computer algebra system Maxima and the interactive geometry software GeoGebra to do the computations and graphics. (Contains 5 figures and 1 note.)

  19. Towards A Grid Infrastructure For Hydro-Meteorological Research

    Directory of Open Access Journals (Sweden)

    Michael Schiffers

    2011-01-01

    Full Text Available The Distributed Research Infrastructure for Hydro-Meteorological Study (DRIHMS is a coordinatedaction co-funded by the European Commission. DRIHMS analyzes the main issuesthat arise when designing and setting up a pan-European Grid-based e-Infrastructure for researchactivities in the hydrologic and meteorological fields. The main outcome of the projectis represented first by a set of Grid usage patterns to support innovative hydro-meteorologicalresearch activities, and second by the implications that such patterns define for a dedicatedGrid infrastructure and the respective Grid architecture.

  20. Modeling land-surface/atmosphere dynamics for CHAMMP

    International Nuclear Information System (INIS)

    Gutowski, W.J. Jr.

    1993-01-01

    Project progress is described on a DOE CHAMP project to model the land-surface/atmosphere coupling in a heterogeneous environment. This work is a collaboration between scientists at Iowa State University and the University of New Hampshire. Work has proceeded in two areas: baseline model coupling and data base development for model validation. The core model elements (land model, atmosphere model) have been ported to the Principal Investigator's computing system and baseline coupling has commenced. The initial target data base is the set of observations from the FIFE field campaign, which is in the process of being acquired. For the remainder of the project period, additional data from the region surrounding the FIFE site and from other field campaigns will be acquired to determine how to best extrapolate results from the initial target region to the rest of the globe. In addition, variants of the coupled model will be used to perform experiments examining resolution requirements and coupling strategies for land-atmosphere coupling in a heterogeneous environment

  1. Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

    Science.gov (United States)

    Vacquie, Laure; Houet, Thomas; Sohl, Terry L.; Reker, Ryan R.; Sayler, Kristi L.

    2015-01-01

    Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

  2. Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

    Science.gov (United States)

    Breuer, L.; Huisman, J.A.; Willems, P.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.

    2009-01-01

    This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model

  3. Modeling green infrastructure land use changes on future air ...

    Science.gov (United States)

    Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteoro

  4. Modeling biofuel expansion effects on land use change dynamics

    International Nuclear Information System (INIS)

    Warner, Ethan; Inman, Daniel; Kunstman, Benjamin; Bush, Brian; Vimmerstedt, Laura; Macknick, Jordan; Zhang Yimin; Peterson, Steve

    2013-01-01

    Increasing demand for crop-based biofuels, in addition to other human drivers of land use, induces direct and indirect land use changes (LUC). Our system dynamics tool is intended to complement existing LUC modeling approaches and to improve the understanding of global LUC drivers and dynamics by allowing examination of global LUC under diverse scenarios and varying model assumptions. We report on a small subset of such analyses. This model provides insights into the drivers and dynamic interactions of LUC (e.g., dietary choices and biofuel policy) and is not intended to assert improvement in numerical results relative to other works. Demand for food commodities are mostly met in high food and high crop-based biofuel demand scenarios, but cropland must expand substantially. Meeting roughly 25% of global transportation fuel demand by 2050 with biofuels requires >2 times the land used to meet food demands under a presumed 40% increase in per capita food demand. In comparison, the high food demand scenario requires greater pastureland for meat production, leading to larger overall expansion into forest and grassland. Our results indicate that, in all scenarios, there is a potential for supply shortfalls, and associated upward pressure on prices, of food commodities requiring higher land use intensity (e.g., beef) which biofuels could exacerbate. (letter)

  5. Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

    Science.gov (United States)

    Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

    2018-02-01

    We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

  6. The Development in modeling Tibetan Plateau Land/Climate Interaction

    Science.gov (United States)

    Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

    2015-04-01

    Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP

  7. Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

    KAUST Repository

    Zampieri, Matteo; Serpetzoglou, Efthymios; Anagnostou, Emmanouil N.; Nikolopoulos, Efthymios I.; Papadopoulos, Anastasios

    2012-01-01

    Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions

  8. Modelling the regional application of stakeholder identified land management strategies.

    Science.gov (United States)

    Irvine, B. J.; Fleskens, L.; Kirkby, M. J.

    2012-04-01

    The DESIRE project has trialled a series of sustainable land management (SLM) technologies. These technologies have been identified as being beneficial in mitigating land degradation by local stakeholders from a range of semi-arid study sites. The field results and the qualitative WOCAT technology assessment ftom across the study sites have been used to develop the adapted PESERA SLM model. This paper considers the development of the adapted PESERA SLM model and the potential for applying locally successful SLM technologies across a wider range of climatic and environmental conditions with respect to degradation risk, biomass production and the investment cost interface (PESERA/DESMICE). The integrate PESERA/DESMICE model contributes to the policy debate by providing a biophysical and socio-economic assessment of technology and policy scenarios.

  9. Central Asia Water (CAWa) - A visualization platform for hydro-meteorological sensor data

    Science.gov (United States)

    Stender, Vivien; Schroeder, Matthias; Wächter, Joachim

    2014-05-01

    Water is an indispensable necessity of life for people in the whole world. In central Asia, water is the key factor for economic development, but is already a narrow resource in this region. In fact of climate change, the water problem handling will be a big challenge for the future. The regional research Network "Central Asia Water" (CAWa) aims at providing a scientific basis for transnational water resources management for the five Central Asia States Kyrgyzstan, Uzbekistan, Tajikistan, Turkmenistan and Kazakhstan. CAWa is part of the Central Asia Water Initiative (also known as the Berlin Process) which was launched by the Federal Foreign Office on 1 April 2008 at the "Water Unites" conference in Berlin. To produce future scenarios and strategies for sustainable water management, data on water reserves and the use of water in Central Asia must therefore be collected consistently across the region. Hydro-meteorological stations equipped with sophisticated sensors are installed in Central Asia and send their data via real-time satellite communication to the operation centre of the monitoring network and to the participating National Hydro-meteorological Services.[1] The challenge for CAWa is to integrate the whole aspects of data management, data workflows, data modeling and visualizations in a proper design of a monitoring infrastructure. The use of standardized interfaces to support data transfer and interoperability is essential in CAWa. An uniform treatment of sensor data can be realized by the OGC Sensor Web Enablement (SWE) , which makes a number of standards and interface definitions available: Observation & Measurement (O&M) model for the description of observations and measurements, Sensor Model Language (SensorML) for the description of sensor systems, Sensor Observation Service (SOS) for obtaining sensor observations, Sensor Planning Service (SPS) for tasking sensors, Web Notification Service (WNS) for asynchronous dialogues and Sensor Alert Service

  10. developing a one stop shop model for integrated land information

    African Journals Online (AJOL)

    DEPT OF AGRICULTURAL ENGINEERING

    which will integrate the data on land ownership, land use and land value for all the land agen- ... services to the investor and other potential clients of land sector agencies involved in the land ..... account types such as a general user, re-.

  11. Dynamic Mesoscale Land-Atmosphere Feedbacks in Fragmented Forests in Amazonia

    Science.gov (United States)

    Rastogi, D.; Baidya Roy, S.

    2011-12-01

    This paper investigates land-atmosphere feedbacks in disturbed rainforests of Amazonia. Deforestation along the rapidly expanding highways and road network has created the unique fishbone land cover pattern in Rondonia, a state in southwestern Amazonia. Numerical experiments and observations show that sharp gradients in land cover due to the fishbone heterogeneity triggers mesoscale circulations. These circulations significantly change the spatial pattern of local hydrometeorology, especially convection, clouds and precipitation. The primary research question now is can these changes in local hydrometeorology affect vegetation growth in the clearings. If so, that would be a clear indication that land-atmosphere feedbacks can affect vegetation recovery in fragmented forests. A computationally-efficient modeling tool consisting of a mesoscale atmospheric model dynamically coupled with a plant growth model has been specifically developed to identify the atmospheric feedback pathways. Preliminary experiments focus on the seasonal-scale feedbacks during the dry season. Results show that temperature, incoming shortwave and precipitation are the three primary drivers through which the feedbacks operate. Increasing temperature increases respiratory losses generating a positive feedback. Increased cloud cover reduces incoming PAR and photosynthesis, resulting in a positive feedback. Increased precipitation reduces water stress and promotes growth resulting in a negative feedback. The net effect is a combination of these 3 feedback loops. These findings can significantly improve our understanding of ecosystem resiliency in disturbed tropical forests.

  12. Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

    Science.gov (United States)

    Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

    2017-11-01

    Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

  13. Model Bera dalam Sistem Agroforestri (Fallow Land Model in Agroforestry Systems

    Directory of Open Access Journals (Sweden)

    Priyono Suryanto

    2011-01-01

    Full Text Available The development of tree-based agroforestry model gives consequences to the space utilization dominated by trees. Farmers take action on this condition by conniving the fallow land. This research was aimed to know the fallow land model, find the key parameters of fallow land model, and formulating the management of fallow land. The spatial model of agroforestry used in this research were trees along border, alley cropping, alternate rows and mixer. The actual data obtained were tree height, tree diameter, crown diameter, land width, and light intensity; the calculated data were land extent, the percentage of crown cover and crown density. The analysis used to determining the percentage of crown cover to calculate the affective arable land area was zone system. Zonation system maked for four zone : 1 zone 1 interval 0-1 m ; 2 zone 2 interval 1-2 m; zone 3 interval 2-3 m; zone 4 interval 3-4m.Key words: agroforestry, fallow land, silviculture, land cover, resource sharing, crown dynamic

  14. Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

    Science.gov (United States)

    Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

    2017-12-01

    Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and

  15. Real estate appraisal of land lots using GAMLSS models

    OpenAIRE

    Florencio, Lutemberg; Cribari-Neto, Francisco; Ospina, Raydonal

    2011-01-01

    The valuation of real estates (e.g., house, land, among others) is of extreme importance for decision making. Their singular characteristics make valuation through hedonic pricing methods dificult since the theory does not specify the correct regression functional form nor which explanatory variables should be included in the hedonic equation. In this article we perform real estate appraisal using a class of regression models proposed by Rigby & Stasinopoulos (2005): generalized additive mode...

  16. Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watersched

    NARCIS (Netherlands)

    Saran, S.; Sterk, G.; Kumar, S.

    2009-01-01

    Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division

  17. Models for estimating runway landing capacity with Microwave Landing System (MLS)

    Science.gov (United States)

    Tosic, V.; Horonjeff, R.

    1975-01-01

    A model is developed which is capable of computing the ultimate landing runway capacity, under ILS and MLS conditions, when aircraft population characteristics and air traffic control separation rules are given. This model can be applied in situations when only a horizontal separation between aircraft approaching a runway is allowed, as well as when both vertical and horizontal separations are possible. It is assumed that the system is free of errors, that is that aircraft arrive at specified points along the prescribed flight path precisely when the controllers intend for them to arrive at these points. Although in the real world there is no such thing as an error-free system, the assumption is adequate for a qualitative comparison of MLS with ILS. Results suggest that an increase in runway landing capacity, caused by introducing the MLS multiple approach paths, is to be expected only when an aircraft population consists of aircraft with significantly differing approach speeds and particularly in situations when vertical separation can be applied. Vertical separation can only be applied if one of the types of aircraft in the mix has a very steep descent angle.

  18. Sustainable Dry Land Management Model on Corn Agribusiness System

    Directory of Open Access Journals (Sweden)

    Yulia Pujiharti

    2008-01-01

    Full Text Available The study aimed at building model of dry land management. Dynamic System Analysis was used to build model and Powersim 2.51 version for simulating. The parameter used in model were fertilizer (urea, SP-36, ACL, productivity (corn, cassava, mungbean, soil nutrient (N, P, K, crop nutrient requirements (corn, cassava, mungbean, mucuna, price (corn, cassava, mungbeans corn flour, feed, urea, SP-36, KCl, food security credit, area planted of (maize, cassava, mungbean, area harvested of (maize, cassava, mungbean, (corn, cassava, mungbean production, wages and farmer income. Sustainable indicator for ecology aspect was soil fertility level, economic aspects were productivity and farmer income, and social aspects were job possibility and traditions. The simulation result indicated that sustainable dry land management can improve soil fertility and increase farmer revenue, became sustainable farming system and farmer society. On the other hand, conventional dry land management decreased soil fertility and yield, caused farmer earnings to decrease and a farm activity could not be continued. Fertilizer distribution did not fulfill farmer requirement, which caused fertilizer scarcity. Food security credit increased fertilizer application. Corn was processed to corn flour or feed to give value added.

  19. Modeling and simulating industrial land-use evolution in Shanghai, China

    Science.gov (United States)

    Qiu, Rongxu; Xu, Wei; Zhang, John; Staenz, Karl

    2018-01-01

    This study proposes a cellular automata-based Industrial and Residential Land Use Competition Model to simulate the dynamic spatial transformation of industrial land use in Shanghai, China. In the proposed model, land development activities in a city are delineated as competitions among different land-use types. The Hedonic Land Pricing Model is adopted to implement the competition framework. To improve simulation results, the Land Price Agglomeration Model was devised to simulate and adjust classic land price theory. A new evolutionary algorithm-based parameter estimation method was devised in place of traditional methods. Simulation results show that the proposed model closely resembles actual land transformation patterns and the model can not only simulate land development, but also redevelopment processes in metropolitan areas.

  20. Hydrometeorological conditions preceding wildfire, and the subsequent burning of a fen watershed in Fort McMurray, Alberta, Canada

    Science.gov (United States)

    Elmes, Matthew C.; Thompson, Dan K.; Sherwood, James H.; Price, Jonathan S.

    2018-01-01

    The destructive nature of the ˜ 590 000 ha Horse river wildfire in the Western Boreal Plain (WBP), northern Alberta, in May of 2016 motivated the investigation of the hydrometeorological conditions that preceded the fire. Historical climate and field hydrometeorological data from a moderate-rich fen watershed were used to (a) identify whether the spring 2016 conditions were outside the range of natural variability for WBP climate cycles, (b) explain the observed patterns in burn severity across the watershed, and (c) identify whether fall and winter moisture signals observed in peatlands and lowland forests in the region are indicative of wildfire. Field hydrometeorological data from the fen watershed confirmed the presence of cumulative moisture deficits prior to the fire. Hydrogeological investigations highlighted the susceptibility of fen and upland areas to water table and soil moisture decline over rain-free periods (including winter), due to the watershed's reliance on supply from localized flow systems originating in topographic highs. Subtle changes in topographic position led to large changes in groundwater connectivity, leading to greater organic soil consumption by fire in wetland margins and at high elevations. The 2016 spring moisture conditions measured prior to the ignition of the fen watershed were not illustrated well by the Drought Code (DC) when standard overwintering procedures were applied. However, close agreement was found when default assumptions were replaced with measured duff soil moisture recharge and incorporated into the overwintering DC procedure. We conclude that accumulated moisture deficits dating back to the summer of 2015 led to the dry conditions that preceded the fire. The infrequent coinciding of several hydrometeorological conditions, including low autumn soil moisture, a modest snowpack, lack of spring precipitation, and high spring air temperatures and winds, ultimately led to the Horse river wildfire spreading widely and

  1. A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

    Science.gov (United States)

    Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhi-Liang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd; Wein, Anne; Liu, Shu-Guang; Kanengieter, Ronald; Acevedo, William

    2012-01-01

    Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

  2. Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

    Science.gov (United States)

    Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

    2012-04-01

    During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and

  3. Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

    Science.gov (United States)

    Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

    2017-12-01

    Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

  4. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    Science.gov (United States)

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  5. Bio-economic farm modelling to analyse agricultural land productivity in Rwanda

    NARCIS (Netherlands)

    Bidogeza, J.C.

    2011-01-01

    Keywords: Rwanda; farm household typology; sustainable technology adoption; multivariate analysis;
    land degradation; food security; bioeconomic model; crop simulation models; organic fertiliser; inorganic fertiliser; policy incentives

    In Rwanda, land degradation contributes to the

  6. A New Conceptual Model for the Continuum of Land Rights | Whittal ...

    African Journals Online (AJOL)

    An aspect of this is land value and the degree of simplicity/complexity in land value is found to be well-aligned with the land rights types in the former continuum model. This is adopted as a suitable substitute for the former measure of informality/formality when locating land rights types on the horizontal axis. Legitimacy ...

  7. Modeling Urban Expansion and Agricultural Land Conversion in Henan Province, China: An Integration of Land Use and Socioeconomic Data

    Directory of Open Access Journals (Sweden)

    Li Jiang

    2016-09-01

    Full Text Available China has experienced rapid urban expansion and agricultural land loss, and the land conversion has accelerated in central provinces since the mid-1990s. The goal of this paper is to examine the relative importance of socioeconomic and policy factors on the urban conversion of agricultural land in Henan Province, China. Using panel econometric models, we examine how socioeconomic and policy factors affect agricultural land conversion at the county level across three time periods, 1995–2000, 2000–2005, and 2005–2010. The results show that both urban land rent and urban wages are essential factors that positively contribute to the conversion of agricultural land. It is also found that per capita GDP is correlated with more urban development and agricultural land loss. Consistent with expectations, agricultural financial support is negatively correlated with agricultural land conversion, suggesting a policy success. Finally, the decomposition analysis illustrates that urban wages are the most influential positive factor and agricultural financial support is the most influential negative factor affecting the urban conversion of agricultural land.

  8. Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

    2017-10-01

    Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

  9. Radiation monitoring of the Slovak Hydrometeorological Institute - Present and future

    International Nuclear Information System (INIS)

    Melicherova, T.

    2008-01-01

    Network for air radioactivity monitoring was developed in the frame Slovak Hydrometeorological Institute (SHMI) since 1963. There are data available for many years for beta radioactivity of the air particulate and deposition. At present network consist from 26 monitoring points for measurement of dose rate and 3 monitoring points for aerosol monitors. Measuring instrument are placed in the professional stations of the selected parts of Slovakia. They are regularly verified and calibrated in the Slovak Institute for Metrology. Radiation monitoring in the SHMI is one part of the Environmental monitoring of Slovakia. All activities and operation of this system are financed from governmental budget of the Environmental monitoring. All information about this system are available on the web page http://enviroportal.sk/ in the part 'Informacny system monitoringu'. (authors)

  10. Radiation monitoring of the Slovak Hydrometeorological Institute - Present and future

    International Nuclear Information System (INIS)

    Melicherova, T.

    2009-01-01

    Network for air radioactivity monitoring was developed in the frame Slovak Hydrometeorological Institute (SHMI) since 1963. There are data available for many years for beta radioactivity of the air particulate and deposition. At present network consist from 26 monitoring points for measurement of dose rate and 3 monitoring points for aerosol monitors. Measuring instrument are placed in the professional stations of the selected parts of Slovakia. They are regularly verified and calibrated in the Slovak Institute for Metrology. Radiation monitoring in the SHMI is one part of the Environmental monitoring of Slovakia. All activities and operation of this system are financed from governmental budget of the Environmental monitoring. All information about this system are available on the web page http://enviroportal.sk/ in the part 'Informacny system monitoringu'. (authors)

  11. Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Huan [University of Maryland, College Park, MD, USA; NASA Goddard Space Flight Center, Greenbelt, MD, USA; Huang, Maoyi [Pacific Northwest National Laboratory, Richland, WA, USA; Tang, Qiuhong [Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; Kirschbaum, Dalia B. [NASA Goddard Space Flight Center, Greenbelt, MD, USA; Ward, Philip [Vrije Universiteit, Amsterdam, Netherlands

    2016-01-01

    Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes, tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards, and society’s vulnerability to them, differs between regions. Severe storms, strong winds, floods and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, and increase propagation of mosquito-borne diseases.

  12. Models meet data: Challenges and opportunities in implementing land management in Earth system models.

    Science.gov (United States)

    Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Kuemmerle, Tobias; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Naudts, Kim

    2018-04-01

    As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land-cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices-forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire-for (1) their importance on the Earth system, (2) the possibility of implementing them in state-of-the-art ESMs, and (3) availability of required input data. Matching these criteria, we identify "low-hanging fruits" for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs. © 2017 John Wiley & Sons Ltd.

  13. Soil Structure - A Neglected Component of Land-Surface Models

    Science.gov (United States)

    Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

    2017-12-01

    Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity

  14. Improving Frozen Precipitation Density Estimation in Land Surface Modeling

    Science.gov (United States)

    Sparrow, K.; Fall, G. M.

    2017-12-01

    The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

  15. A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

    Science.gov (United States)

    Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

    2018-01-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

    Science.gov (United States)

    Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

    2014-01-01

    As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model

  17. Representing Reservoir Stratification in Land Surface and Earth System Models

    Science.gov (United States)

    Yigzaw, W.; Li, H. Y.; Leung, L. R.; Hejazi, M. I.; Voisin, N.; Payn, R. A.; Demissie, Y.

    2017-12-01

    A one-dimensional reservoir stratification modeling has been developed as part of Model for Scale Adaptive River Transport (MOSART), which is the river transport model used in the Accelerated Climate Modeling for Energy (ACME) and Community Earth System Model (CESM). Reservoirs play an important role in modulating the dynamic water, energy and biogeochemical cycles in the riverine system through nutrient sequestration and stratification. However, most earth system models include lake models that assume a simplified geometry featuring a constant depth and a constant surface area. As reservoir geometry has important effects on thermal stratification, we developed a new algorithm for deriving generic, stratified area-elevation-storage relationships that are applicable at regional and global scales using data from Global Reservoir and Dam database (GRanD). This new reservoir geometry dataset is then used to support the development of a reservoir stratification module within MOSART. The mixing of layers (energy and mass) in the reservoir is driven by eddy diffusion, vertical advection, and reservoir inflow and outflow. Upstream inflow into a reservoir is treated as an additional source/sink of energy, while downstream outflow represented a sink. Hourly atmospheric forcing from North American Land Assimilation System (NLDAS) Phase II and simulated daily runoff by ACME land component are used as inputs for the model over the contiguous United States for simulations between 2001-2010. The model is validated using selected observed temperature profile data in a number of reservoirs that are subject to various levels of regulation. The reservoir stratification module completes the representation of riverine mass and heat transfer in earth system models, which is a major step towards quantitative understanding of human influences on the terrestrial hydrological, ecological and biogeochemical cycles.

  18. Research on the decision-making model of land-use spatial optimization

    Science.gov (United States)

    He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

    2009-10-01

    Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

  19. Population Density Modeling for Diverse Land Use Classes: Creating a National Dasymetric Worker Population Model

    Science.gov (United States)

    Trombley, N.; Weber, E.; Moehl, J.

    2017-12-01

    Many studies invoke dasymetric mapping to make more accurate depictions of population distribution by spatially restricting populations to inhabited/inhabitable portions of observational units (e.g., census blocks) and/or by varying population density among different land classes. LandScan USA uses this approach by restricting particular population components (such as residents or workers) to building area detected from remotely sensed imagery, but also goes a step further by classifying each cell of building area in accordance with ancillary land use information from national parcel data (CoreLogic, Inc.'s ParcelPoint database). Modeling population density according to land use is critical. For instance, office buildings would have a higher density of workers than warehouses even though the latter would likely have more cells of detection. This paper presents a modeling approach by which different land uses are assigned different densities to more accurately distribute populations within them. For parts of the country where the parcel data is insufficient, an alternate methodology is developed that uses National Land Cover Database (NLCD) data to define the land use type of building detection. Furthermore, LiDAR data is incorporated for many of the largest cities across the US, allowing the independent variables to be updated from two-dimensional building detection area to total building floor space. In the end, four different regression models are created to explain the effect of different land uses on worker distribution: A two-dimensional model using land use types from the parcel data A three-dimensional model using land use types from the parcel data A two-dimensional model using land use types from the NLCD data, and A three-dimensional model using land use types from the NLCD data. By and large, the resultant coefficients followed intuition, but importantly allow the relationships between different land uses to be quantified. For instance, in the model

  20. Hydro-meteorological extreme events in the 18th century in Portugal

    Science.gov (United States)

    Fragoso, Marcelo; João Alcoforado, Maria; Taborda, João Paulo

    2013-04-01

    The present work is carried out in the frame of the KLIMHIST PROJECT ("Reconstruction and model simulations of past climate in Portugal using documentary and early instrumental sources, 17th-19th century)", and is devoted to the study of hydro-meteorological extreme events during the last 350 years, in order to understand how they have changed in time and compare them with current analogues. More specifically, the results selected to this presentation will focus on some hydro-meteorological extreme events of the 18th century, like severe droughts, heavy precipitation episodes and windstorms. One of the most noteworthy events was the winterstorm Bárbara (3rd to 6th December 1739), already studied in prior investigations (Taborda et al, 2004; Pfister et al, 2010), a devastating storm with strong impacts in Portugal caused by violent winds and heavy rainfall. Several other extreme events were detected by searching different documentary archives, including individual, administrative and ecclesiastic sources. Moreover, a more detailed insight to the 1783-1787 period will be made with regard the Lisbon region, taking into consideration the availability of information for daily meteorological observations as well as documentary evidences, like descriptions from Gazeta de Lisboa, the periodic with more continuous publication in the 18thcentury. Key-words: Instrumental data, Documentary data, Extreme events, Klimhist Project, Portugal References Pfister, C., Garnier, E., Alcoforado, M.J., Wheeler, D. Luterbacher, J. Nunes, M.F., Taborda, J.P. (2010) The meteorological framework and the cultural memory of three severe winter-storms in early eighteenth-century Europe, Climatic Change, 101, 1-2, 281-310 Taborda, JP; Alcoforado, MJ and Garcia, JC (2004) O Clima do Sul de Portugal no Séc.XVIII, Centro de Estudos Geográficos, Área de de Investigação de Geo-Ecologia, relatório no 2

  1. MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS

    Directory of Open Access Journals (Sweden)

    A. M. Bernales

    2016-06-01

    Full Text Available The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC and land surface temperature (LST. Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas and looking for common predictors between LSTs of these two different farming periods.

  2. Radar-driven High-resolution Hydrometeorological Forecasts of the 26 September 2007 Venice flash flood

    Science.gov (United States)

    Massimo Rossa, Andrea; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

    2010-05-01

    Space and time scales of flash floods are such that flash flood forecasting and warning systems depend upon the accurate real-time provision of rainfall information, high-resolution numerical weather prediction (NWP) forecasts and the use of hydrological models. Currently available high-resolution NWP model models can potentially provide warning forecasters information on the future evolution of storms and their internal structure, thereby increasing convective-scale warning lead times. However, it is essential that the model be started with a very accurate representation of on-going convection, which calls for assimilation of high-resolution rainfall data. This study aims to assess the feasibility of using carefully checked radar-derived quantitative precipitation estimates (QPE) for assimilation into NWP and hydrological models. The hydrometeorological modeling chain includes the convection-permitting NWP model COSMO-2 and a hydrologic-hydraulic models built upon the concept of geomorphological transport. Radar rainfall observations are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood event which impacted the coastal area of north-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the Dese river, a 90 km2 catchment flowing to the Venice lagoon. The radar rainfall observations are carefully checked for artifacts, including beam attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar QPE in the assimilation cycle of the NWP model is very significant, in that the main individual organized convective systems were successfully introduced into the model state, both in terms of timing and localization. Also, incorrectly localized precipitation in the model reference run without rainfall assimilation was correctly reduced to about the observed levels. On the other hand, the

  3. Using Backcast Land-Use Change and Groundwater Travel-Time Models to Generate Land-Use Legacy Maps for Watershed Management

    OpenAIRE

    Bryan Pijanowski; Deepak K. Ray; Anthony D. Kendall; Jonah M. Duckles; David W. Hyndman

    2007-01-01

    We couple two spatial-temporal models, a backcast land-use change model and a groundwater flow model, to develop what we call "land-use legacy maps." We quantify how a land-use legacy map, created from maps of past land use and groundwater travel times, differs from a current land-use map. We show how these map differences can affect land-use planning and watershed management decisions at a variety of spatial and temporal scales. Our approach demonstrates that land-use legacy maps provide a m...

  4. Launch and Landing Effects Ground Operations (LLEGO) Model

    Science.gov (United States)

    2008-01-01

    LLEGO is a model for understanding recurring launch and landing operations costs at Kennedy Space Center for human space flight. Launch and landing operations are often referred to as ground processing, or ground operations. Currently, this function is specific to the ground operations for the Space Shuttle Space Transportation System within the Space Shuttle Program. The Constellation system to follow the Space Shuttle consists of the crewed Orion spacecraft atop an Ares I launch vehicle and the uncrewed Ares V cargo launch vehicle. The Constellation flight and ground systems build upon many elements of the existing Shuttle flight and ground hardware, as well as upon existing organizations and processes. In turn, the LLEGO model builds upon past ground operations research, modeling, data, and experience in estimating for future programs. Rather than to simply provide estimates, the LLEGO model s main purpose is to improve expenses by relating complex relationships among functions (ground operations contractor, subcontractors, civil service technical, center management, operations, etc.) to tangible drivers. Drivers include flight system complexity and reliability, as well as operations and supply chain management processes and technology. Together these factors define the operability and potential improvements for any future system, from the most direct to the least direct expenses.

  5. Bioenergy Ecosystem Land-Use Modelling and Field Flux Trial

    Science.gov (United States)

    McNamara, Niall; Bottoms, Emily; Donnison, Iain; Dondini, Marta; Farrar, Kerrie; Finch, Jon; Harris, Zoe; Ineson, Phil; Keane, Ben; Massey, Alice; McCalmont, Jon; Morison, James; Perks, Mike; Pogson, Mark; Rowe, Rebecca; Smith, Pete; Sohi, Saran; Tallis, Mat; Taylor, Gail; Yamulki, Sirwan

    2013-04-01

    Climate change impacts resulting from fossil fuel combustion and concerns about the diversity of energy supply are driving interest to find low-carbon energy alternatives. As a result bioenergy is receiving widespread scientific, political and media attention for its potential role in both supplying energy and mitigating greenhouse (GHG) emissions. It is estimated that the bioenergy contribution to EU 2020 renewable energy targets could require up to 17-21 million hectares of additional land in Europe (Don et al., 2012). There are increasing concerns that some transitions into bioenergy may not be as sustainable as first thought when GHG emissions from the crop growth and management cycle are factored into any GHG life cycle assessment (LCA). Bioenergy is complex and encapsulates a wide range of crops, varying from food crop based biofuels to dedicated second generation perennial energy crops and forestry products. The decision on the choice of crop for energy production significantly influences the GHG mitigation potential. It is recognised that GHG savings or losses are in part a function of the original land-use that has undergone change and the management intensity for the energy crop. There is therefore an urgent need to better quantify both crop and site-specific effects associated with the production of conventional and dedicated energy crops on the GHG balance. Currently, there is scarcity of GHG balance data with respect to second generation crops meaning that process based models and LCAs of GHG balances are weakly underpinned. Therefore, robust, models based on real data are urgently required. In the UK we have recently embarked on a detailed program of work to address this challenge by combining a large number of field studies with state-of-the-art process models. Through six detailed experiments, we are calculating the annual GHG balances of land use transitions into energy crops across the UK. Further, we are quantifying the total soil carbon gain or

  6. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  7. Predictive Modeling for NASA Entry, Descent and Landing Missions

    Science.gov (United States)

    Wright, Michael

    2016-01-01

    Entry, Descent and Landing (EDL) Modeling and Simulation (MS) is an enabling capability for complex NASA entry missions such as MSL and Orion. MS is used in every mission phase to define mission concepts, select appropriate architectures, design EDL systems, quantify margin and risk, ensure correct system operation, and analyze data returned from the entry. In an environment where it is impossible to fully test EDL concepts on the ground prior to use, accurate MS capability is required to extrapolate ground test results to expected flight performance.

  8. Integrating global socio-economic influences into a regional land use change model for China

    Science.gov (United States)

    Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

    2014-03-01

    With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

  9. Mapping the global depth to bedrock for land surface modelling

    Science.gov (United States)

    Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

    2017-12-01

    Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

  10. Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

    Science.gov (United States)

    Spruce, J.; Bolten, J. D.; Srinivasan, R.

    2017-12-01

    This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling

  11. Reliable low precision simulations in land surface models

    Science.gov (United States)

    Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

    2017-12-01

    Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

  12. EXPERT MODEL OF LAND SUITABILITY ASSESSMENT FOR CROPS

    Directory of Open Access Journals (Sweden)

    Boris Đurđević

    2010-12-01

    Full Text Available A total of 17404 soil samples (2003rd-2009th year were analysed in the eastern Croatia. The largest number of soil samples belongs to the Osijek-Baranya county, which together with both Eastern sugar beet Factories (Osijek and Županja, conduct the soil fertility control (~4200 samples/yr.. Computer model suitability assessment for crops, supported by GIS, proved to be fast, efficient enough reliable in terms of the number of analyzed soil samples. It allows the visualization of the agricultural area and prediction of its production properties for the purposes of analysis, planning and rationalization of agricultural production. With more precise data about the soil (soil, climate and reliable Digital Soil Map of Croatia, the model could be an acceptable, not only to evaluate the suitability for growing different crops but also their need for fertilizer, necessary machinery, repairs (liming, and other measures of organic matter input. The abovementioned aims to eliminate or reduce effects of limiting factors in primary agricultural production. Assessment of the relative benefits of soil presented by computer model for the crops production and geostatistical method kriging in the Osijek-Baranya county showed: 1 Average soil suitability being 60.06 percent. 2 Kriging predicted that 51751 ha (17.16% are of limited resources (N1 for growing crops whereas a 86142 ha (28.57% of land is limited suitably (S3, b 132789 ha (44.04% are moderately suitable (S2 and c 30772 ha (10.28% are of excellent fertility (S1. A large number of eastern Croatian land data showed that the computer-geostatistical model for determination of soil benefits for growing crops was automated, fast and simple to use and suitable for the implementation of GIS and automatically downloading the necessary benefit indicators from the input base (land, analytical and climate as well as data from the digital soil maps able to: a visualize the suitability for soil tillage, b predict the

  13. Improved Hydrology over Peatlands in a Global Land Modeling System

    Science.gov (United States)

    Bechtold, M.; Delannoy, G.; Reichle, R.; Koster, R.; Mahanama, S.; Roose, Dirk

    2018-01-01

    Peatlands of the Northern Hemisphere represent an important carbon pool that mainly accumulated since the last ice age under permanently wet conditions in specific geological and climatic settings. The carbon balance of peatlands is closely coupled to water table dynamics. Consequently, the future carbon balance over peatlands is strongly dependent on how hydrology in peatlands will react to changing boundary conditions, e.g. due to climate change or regional water level drawdown of connected aquifers or streams. Global land surface modeling over organic-rich regions can provide valuable global-scale insights on where and how peatlands are in transition due to changing boundary conditions. However, the current global land surface models are not able to reproduce typical hydrological dynamics in peatlands well. We implemented specific structural and parametric changes to account for key hydrological characteristics of peatlands into NASA's GEOS-5 Catchment Land Surface Model (CLSM, Koster et al. 2000). The main modifications pertain to the modeling of partial inundation, and the definition of peatland-specific runoff and evapotranspiration schemes. We ran a set of simulations on a high performance cluster using different CLSM configurations and validated the results with a newly compiled global in-situ dataset of water table depths in peatlands. The results demonstrate that an update of soil hydraulic properties for peat soils alone does not improve the performance of CLSM over peatlands. However, structural model changes for peatlands are able to improve the skill metrics for water table depth. The validation results for the water table depth indicate a reduction of the bias from 2.5 to 0.2 m, and an improvement of the temporal correlation coefficient from 0.5 to 0.65, and from 0.4 to 0.55 for the anomalies. Our validation data set includes both bogs (rain-fed) and fens (ground and/or surface water influence) and reveals that the metrics improved less for fens. In

  14. ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE

    Directory of Open Access Journals (Sweden)

    Z. Zou

    2017-09-01

    Full Text Available Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.

  15. Shallow to Deep Convection Transition over a Heterogeneous Land Surface Using the Land Model Coupled Large-Eddy Simulation

    Science.gov (United States)

    Lee, J.; Zhang, Y.; Klein, S. A.

    2017-12-01

    The triggering of the land breeze, and hence the development of deep convection over heterogeneous land should be understood as a consequence of the complex processes involving various factors from land surface and atmosphere simultaneously. That is a sub-grid scale process that many large-scale models have difficulty incorporating it into the parameterization scheme partly due to lack of our understanding. Thus, it is imperative that we approach the problem using a high-resolution modeling framework. In this study, we use SAM-SLM (Lee and Khairoutdinov, 2015), a large-eddy simulation model coupled to a land model, to explore the cloud effect such as cold pool, the cloud shading and the soil moisture memory on the land breeze structure and the further development of cloud and precipitation over a heterogeneous land surface. The atmospheric large scale forcing and the initial sounding are taken from the new composite case study of the fair-weather, non-precipitating shallow cumuli at ARM SGP (Zhang et al., 2017). We model the land surface as a chess board pattern with alternating leaf area index (LAI). The patch contrast of the LAI is adjusted to encompass the weak to strong heterogeneity amplitude. The surface sensible- and latent heat fluxes are computed according to the given LAI representing the differential surface heating over a heterogeneous land surface. Separate from the surface forcing imposed from the originally modeled surface, the cases that transition into the moist convection can induce another layer of the surface heterogeneity from the 1) radiation shading by clouds, 2) adjusted soil moisture pattern by the rain, 3) spreading cold pool. First, we assess and quantifies the individual cloud effect on the land breeze and the moist convection under the weak wind to simplify the feedback processes. And then, the same set of experiments is repeated under sheared background wind with low level jet, a typical summer time wind pattern at ARM SGP site, to

  16. Land use and land cover change based on historical space-time model

    Science.gov (United States)

    Sun, Qiong; Zhang, Chi; Liu, Min; Zhang, Yongjing

    2016-09-01

    Land use and cover change is a leading edge topic in the current research field of global environmental changes and case study of typical areas is an important approach understanding global environmental changes. Taking the Qiantang River (Zhejiang, China) as an example, this study explores automatic classification of land use using remote sensing technology and analyzes historical space-time change by remote sensing monitoring. This study combines spectral angle mapping (SAM) with multi-source information and creates a convenient and efficient high-precision land use computer automatic classification method which meets the application requirements and is suitable for complex landform of the studied area. This work analyzes the histological space-time characteristics of land use and cover change in the Qiantang River basin in 2001, 2007 and 2014, in order to (i) verify the feasibility of studying land use change with remote sensing technology, (ii) accurately understand the change of land use and cover as well as historical space-time evolution trend, (iii) provide a realistic basis for the sustainable development of the Qiantang River basin and (iv) provide a strong information support and new research method for optimizing the Qiantang River land use structure and achieving optimal allocation of land resources and scientific management.

  17. Water cycle research associated with the CaPE hydrometeorology project (CHymP

    Science.gov (United States)

    Duchon, Claude E.

    1993-01-01

    One outgrowth of the Convection and Precipitation/Electrification (CaPE) experiment that took place in central Florida during July and August 1991 was the creation of the CaPE Hydrometeorology Project (CHymP). The principal goal of this project is to investigate the daily water cycle of the CaPE experimental area by analyzing the numerous land and atmosphere in situ and remotely sensed data sets that were generated during the 40-days of observations. The water cycle comprises the atmospheric branch. In turn, the atmospheric branch comprises precipitation leaving the base of the atmospheric volume under study, evaporation and transpiration entering the base, the net horizontal fluxes of water vapor and cloud water through the volume and the conversion of water vapor to cloud water and vice-versa. The sum of these components results in a time rate of change in the water and liquid water (or ice) content of the atmospheric volume. The components of the land branch are precipitation input to and evaporation and transpiration output from the surface, net horizontal fluxes of surface and subsurface water, the sum of which results in a time rate of change in surface and subsurface water mass. The objective of CHymP is to estimate these components in order to determine the daily water budget for a selected area within the CaPE domain. This work began in earnest in the summer of 1992 and continues. Even estimating all the budget components for one day is a complex and time consuming task. The discussions below provides a short summary of the rainfall quality assessment procedures followed by a plan for estimating the horizontal moisture flux.

  18. A Local Land Use Competition Cellular Automata Model and Its Application

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2016-06-01

    Full Text Available Cellular automaton (CA is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making.

  19. Physics-based Entry, Descent and Landing Risk Model

    Science.gov (United States)

    Gee, Ken; Huynh, Loc C.; Manning, Ted

    2014-01-01

    A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

  20. Quantifying and Analysing Neighbourhood Characteristics Supporting Urban Land-Use Modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2009-01-01

    Land-use modelling and spatial scenarios have gained increased attention as a means to meet the challenge of reducing uncertainty in the spatial planning and decision-making. Several organisations have developed software for land-use modelling. Many of the recent modelling efforts incorporate...... cellular automata (CA) to accomplish spatially explicit land-use change modelling. Spatial interaction between neighbour land-uses is an important component in urban cellular automata. Nevertheless, this component is calibrated through trial-and-error estimation. The aim of the current research project has...... been to quantify and analyse land-use neighbourhood characteristics and impart useful information for cell based land-use modelling. The results of our research is a major step forward, because we have estimated rules for neighbourhood interaction from really observed land-use changes at a yearly basis...

  1. A New Conceptual Model for the Continuum of Land Rights

    African Journals Online (AJOL)

    Akrofi

    “A theory which proposes that long-term social change happens in stages, that it is linear, ..... Shaw (2013, 169) who proposes a “new socially determined formality” to bridge the divide between .... between land rights and land tenure security with a focus on improving land tenure security, ..... cohesion, memory, trust, status ...

  2. Land-Use Portfolio Modeler, Version 1.0

    Science.gov (United States)

    Taketa, Richard; Hong, Makiko

    2010-01-01

    -on-investment. The portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different

  3. Bayesian calibration of the Community Land Model using surrogates

    Energy Technology Data Exchange (ETDEWEB)

    Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Swiler, Laura Painton

    2014-02-01

    We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural error in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.

  4. Global Land Use Regression Model for Nitrogen Dioxide Air Pollution.

    Science.gov (United States)

    Larkin, Andrew; Geddes, Jeffrey A; Martin, Randall V; Xiao, Qingyang; Liu, Yang; Marshall, Julian D; Brauer, Michael; Hystad, Perry

    2017-06-20

    Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO 2 exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO 2 ) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO 2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R 2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R 2 within 2%) but not for Africa and Oceania (adjusted R 2 within 11%) where NO 2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO 2 concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO 2 were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO 2 monitoring data or models.

  5. The missing biology in land carbon models (Invited)

    Science.gov (United States)

    Prentice, I. C.; Cornwell, W.; Dong, N.; Maire, V.; Wang, H.; Wright, I.

    2013-12-01

    Models of terrestrial carbon cycling give divergent results, and recent developments - notably the inclusion of nitrogen-carbon cycle coupling - have apparently made matters worse. More extensive benchmarking of models would be highly desirable, but is not a panacea. Problems with current models include overparameterization (assigning separate sets of parameter values for each plant functional type can easily obscure more fundamental model limitations), and the widespread persistence of incorrect paradigms to describe plant responses to environment. Next-generation models require a more sound basis in observations and theory. A possible way forward will be outlined. It will be shown how the principle of optimization by natural selection can yield testable, general hypotheses about plant function. A specific optimality hypothesis about the control of CO2 drawdown versus water loss by leaves will be shown to yield global and quantitatively verifable predictions of plant behaviour as demonstrated in field gas-exchange measurements across species from different environments, and in the global pattern of stable carbon isotope discrimination by plants. Combined with the co-limitation hypothesis for the control of photosynthetic capacity and an economic approach to the costs of nutrient acquisition, this hypothesis provides a potential foundation for a comprehensive predictive understanding of the controls of primary production on land.

  6. Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis

    Science.gov (United States)

    J Jeuck; F. Cubbage; R. Abt; R. Bardon; J. McCarter; J. Coulston; M. Renkow

    2014-01-01

    : We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland 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...

  7. Hydrometeorological extremes and their impacts derived from taxation records for south-eastern Moravia (Czech Republic) in the period 1751-1900

    Science.gov (United States)

    Chromá, K.; Brázdil, R.; Valášek, H.; Dolák, L.

    2012-04-01

    Hydrometeorological extremes always influenced human activities and caused great material damage or even loss of human lives. In the Czech Lands (recently the Czech Republic), systematic meteorological and hydrological observations started generally in the latter half of the 19th century. In order to create long-term series of hydrometeorological extremes, it is necessary to search for other sources of information for their study before 1850. In this study, written records associated with tax relief at ten estates located in south-eastern Moravia are used for the study of hydrometeorological extremes and their impacts during the period 1751-1900. The taxation system in Moravia allowed farmers to request tax relief if their crop yields had been negatively affected by hydrological and meteorological extremes. The documentation involved contains information about the type of extreme event and the date of its occurrence, and the impacts on crops may often be derived. A total of 175 extreme events resulting in some kind of damage is documented for 1751-1900, with the highest concentration between 1811 and 1860. The nature of events leading to damage (of a possible 272 types) include hailstorm (25.7%), torrential rain (21.7%), and flood (21.0%), followed by thunderstorm, flash flood, late frost and windstorm. The four most outstanding events, affecting the highest number of settlements, were thunderstorms with hailstorms (25 June 1825, 20 May 1847 and 29 June 1890) and flooding of the River Morava (mid-June 1847). Hydrometeorological extremes in the 1816-1855 period are compared with those occurring during the recent 1961-2000 period. The results obtained are inevitably influenced by uncertainties related to taxation records, such as their temporal and spatial incompleteness, the limits of the period of outside agricultural work (i.e. mainly May-August) and the purpose for which they were originally collected (primarily tax alleviation, i.e. information about

  8. Spatial Modelling of Land Price in The Semarang City

    Science.gov (United States)

    Widjonarko, W.

    2018-02-01

    Land has a very important role in supporting the population activity in both urban and rural areas. Demand for land tends to increase due to the increase in population, on the other hand the availability of land is limited. The increasing demand of land also occurred in the city of Semarang due to population growth and economic activity growth. The increasing demand for land in Semarang City has caused a shift in spatial demand patterns. The shift in land demand is due to limited supply of land in the area near to the city center, and the price become unaffordable for some residents of Semarang City. Due to the limitation of land supply in the city center has affected to the increasing demand of land in the suburbs. This phenomenon causes an increase in the price of land in the periphery of Semarang, and forms a land price pattern that resembles a circus tent, especially at a new center of activity on the periphery.

  9. Revisiting Kappa to account for change in the accuracy assessment of land-use models

    NARCIS (Netherlands)

    Vliet, van J.; Bregt, A.K.; Hagen-Zanker, A.

    2011-01-01

    Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the

  10. Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

    Science.gov (United States)

    Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

    2014-01-01

    Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

  11. Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

    Directory of Open Access Journals (Sweden)

    Nicholas R Magliocca

    Full Text Available Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model

  12. Assessment extreme hydrometeorological conditions in the Gulf of Bothnia, the Baltic Sea

    Science.gov (United States)

    Dvornikov, Anton; Martyanov, Stanislav; Ryabchenko, Vladimir; Eremina, Tatjana; Isaev, Alexey; Sein, Dmitry

    2017-04-01

    Extreme hydrometeorological conditions in the Gulf of Bothnia, the Baltic Sea, are estimated paying a special attention to the area of the future construction of nuclear power plant (NPP) "Hanhikivi-1" (24° 16' E, 64° 32' N). To produce these estimates, long-term observations and results from numerical models of water and ice circulation and wind waves are used. It is estimated that the average annual air temperature in the vicinity of the station is +3° C, summer and winter extreme temperature is equal to 33.3° C and -41.5° C, respectively. Model calculations of wind waves have shown that the most dangerous (in terms of the generation of wind waves in the NPP area) is a north-west wind with the direction of 310°. The maximum height of the waves in the Gulf of Bothnia near the NPP for this wind direction with wind velocity of 10 m/s is 1.2-1.4 m. According to the model estimates, the highest possible level of the sea near the NPP is 248 cm, the minimum level, -151 cm, respectively for the western and eastern winds. These estimates are in good agreement with observations on the sea level for the period 1922-2015 at the nearest hydrometeorological station Raahe (Finland). In order to assess the likely impact of the NPP on the marine environment numerical experiments for the cold (2010) and warm year (2014) have been carried out. These calculations have shown that permanent release of heat into the marine environment from the operating NPP for the cold year (2010) will increase the temperature in the upper layer of 0-250m zone by 10°C in winter - spring and by 8°C in summer - early autumn, and in the bottom layer of 0-250m zone by 5°C in winter - spring and 3°C in summer - early autumn. For the warm year (2014), these temperature changes are smaller. Ice cover in both cases will disappear in two - kilometer vicinity of the NPP. These effects should be taken into account when assessing local climate changes in the future

  13. Combining emperical and theory-based land use modelling approaches to assess future availability of land and economic potential for sustainable biofuel production: Argentina as a case study

    NARCIS (Netherlands)

    Diogo, V.; van der Hilst, Floortje; van Eijck, Janske; Faaij, André; Verstegen, Judith; Hilbert, J.; Carballo, S.; Volante, J.

    2014-01-01

    In this paper, a land-use modelling framework is presented combining empirical and theory-based modelling approaches to determine economic potential of biofuel production avoiding indirect land-use changes (iLUC) resulting from land competition with other functions. The empirical approach explores

  14. Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

    2010-01-01

    Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

  15. Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

    Science.gov (United States)

    Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

    1997-01-01

    The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface

  16. Land surface evapotranspiration modelling at the regional scale

    Science.gov (United States)

    Raffelli, Giulia; Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Gisolo, Davide; Provenzale, Antonello

    2017-04-01

    Climate change has relevant implications for the environment, water resources and human life in general. The observed increment of mean air temperature, in addition to a more frequent occurrence of extreme events such as droughts, may have a severe effect on the hydrological cycle. Besides climate change, land use changes are assumed to be another relevant component of global change in terms of impacts on terrestrial ecosystems: socio-economic changes have led to conversions between meadows and pastures and in most cases to a complete abandonment of grasslands. Water is subject to different physical processes among which evapotranspiration (ET) is one of the most significant. In fact, ET plays a key role in estimating crop growth, water demand and irrigation water management, so estimating values of ET can be crucial for water resource planning, irrigation requirement and agricultural production. Potential evapotranspiration (PET) is the amount of evaporation that occurs when a sufficient water source is available. It can be estimated just knowing temperatures (mean, maximum and minimum) and solar radiation. Actual evapotranspiration (AET) is instead the real quantity of water which is consumed by soil and vegetation; it is obtained as a fraction of PET. The aim of this work was to apply a simplified hydrological model to calculate AET for the province of Turin (Italy) in order to assess the water content and estimate the groundwater recharge at a regional scale. The soil is seen as a bucket (FAO56 model, Allen et al., 1998) made of different layers, which interact with water and vegetation. The water balance is given by precipitations (both rain and snow) and dew as positive inputs, while AET, runoff and drainage represent the rate of water escaping from soil. The difference between inputs and outputs is the water stock. Model data inputs are: soil characteristics (percentage of clay, silt, sand, rocks and organic matter); soil depth; the wilting point (i.e. the

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

    Science.gov (United States)

    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

  18. Coupling a groundwater model with a land surface model to improve water and energy cycle simulation

    Directory of Open Access Journals (Sweden)

    W. Tian

    2012-12-01

    Full Text Available Water and energy cycles interact, making these two processes closely related. Land surface models (LSMs can describe the water and energy cycles on the land surface, but their description of the subsurface water processes is oversimplified, and lateral groundwater flow is ignored. Groundwater models (GWMs describe the dynamic movement of the subsurface water well, but they cannot depict the physical mechanisms of the evapotranspiration (ET process in detail. In this study, a coupled model of groundwater flow with a simple biosphere (GWSiB is developed based on the full coupling of a typical land surface model (SiB2 and a 3-D variably saturated groundwater model (AquiferFlow. In this coupled model, the infiltration, ET and energy transfer are simulated by SiB2 using the soil moisture results from the groundwater flow model. The infiltration and ET results are applied iteratively to drive the groundwater flow model. After the coupled model is built, a sensitivity test is first performed, and the effect of the groundwater depth and the hydraulic conductivity parameters on the ET are analyzed. The coupled model is then validated using measurements from two stations located in shallow and deep groundwater depth zones. Finally, the coupled model is applied to data from the middle reach of the Heihe River basin in the northwest of China to test the regional simulation capabilities of the model.

  19. Ecological Assimilation of Land and Climate Observations - the EALCO model

    Science.gov (United States)

    Wang, S.; Zhang, Y.; Trishchenko, A.

    2004-05-01

    Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net

  20. An End-to-End System to Enable Quick, Easy and Inexpensive Deployment of Hydrometeorological Stations

    Science.gov (United States)

    Celicourt, P.; Piasecki, M.

    2014-12-01

    The high cost of hydro-meteorological data acquisition, communication and publication systems along with limited qualified human resources is considered as the main reason why hydro-meteorological data collection remains a challenge especially in developing countries. Despite significant advances in sensor network technologies which gave birth to open hardware and software, low-cost (less than $50) and low-power (in the order of a few miliWatts) sensor platforms in the last two decades, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome, and thus expensive task. These factors give rise for the need to develop a affordable, simple to deploy, scalable and self-organizing end-to-end (from sensor to publication) system suitable for deployment in such countries. The design of the envisioned system will consist of a few Sensed-And-Programmed Arduino-based sensor nodes with low-cost sensors measuring parameters relevant to hydrological processes and a Raspberry Pi micro-computer hosting the in-the-field back-end data management. This latter comprises the Python/Django model of the CUAHSI Observations Data Model (ODM) namely DjangODM backed by a PostgreSQL Database Server. We are also developing a Python-based data processing script which will be paired with the data autoloading capability of Django to populate the DjangODM database with the incoming data. To publish the data, the WOFpy (WaterOneFlow Web Services in Python) developed by the Texas Water Development Board for 'Water Data for Texas' which can produce WaterML web services from a variety of back-end database installations such as SQLite, MySQL, and PostgreSQL will be used. A step further would be the development of an appealing online visualization tool using Python statistics and analytics tools (Scipy, Numpy, Pandas) showing the spatial distribution of variables across an entire watershed as a time variant layer on top of a basemap.

  1. Adapting observationally based metrics of biogeophysical feedbacks from land cover/land use change to climate modeling

    International Nuclear Information System (INIS)

    Chen, Liang; Dirmeyer, Paul A

    2016-01-01

    To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land–atmosphere interactions in response to LCLUC. (letter)

  2. Modeling Forest Succession among Ecological Land Units in Northern Minnesota

    Directory of Open Access Journals (Sweden)

    George Host

    1998-12-01

    Full Text Available Field and modeling studies were used to quantify potential successional pathways among fine-scale ecological classification units within two geomorphic regions of north-central Minnesota. Soil and overstory data were collected on plots stratified across low-relief ground moraines and undulating sand dunes. Each geomorphic feature was sampled across gradients of topography or soil texture. Overstory conditions were sampled using five variable-radius point samples per plot; soil samples were analyzed for carbon and nitrogen content. Climatic, forest composition, and soil data were used to parameterize the sample plots for use with LINKAGES, a forest growth model that simulates changes in composition and soil characteristics over time. Forest composition and soil properties varied within and among geomorphic features. LINKAGES simulations were using "bare ground" and the current overstory as starting conditions. Northern hardwoods or pines dominated the late-successional communities of morainal and dune landforms, respectively. The morainal landforms were dominated by yellow birch and sugar maple; yellow birch reached its maximum abundance in intermediate landscape positions. On the dune sites, pine was most abundant in drier landscape positions, with white spruce increasing in abundance with increasing soil moisture and N content. The differences in measured soil properties and predicted late-successional composition indicate that ecological land units incorporate some of the key variables that govern forest composition and structure. They further show the value of ecological classification and modeling for developing forest management strategies that incorporate the spatial and temporal dynamics of forest ecosystems.

  3. SMOS brightness temperature assimilation into the Community Land Model

    Directory of Open Access Journals (Sweden)

    D. Rains

    2017-11-01

    Full Text Available SMOS (Soil Moisture and Ocean Salinity mission brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF as well as to the Community Microwave Emission Model (CMEM. Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010–2015. Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 % for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

  4. Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds

    Science.gov (United States)

    Bogaard, Thom; Greco, Roberto

    2018-01-01

    Many shallow landslides and debris flows are precipitation initiated. Therefore, regional landslide hazard assessment is often based on empirically derived precipitation intensity-duration (ID) thresholds and landslide inventories. Generally, two features of precipitation events are plotted and labeled with (shallow) landslide occurrence or non-occurrence. Hereafter, a separation line or zone is drawn, mostly in logarithmic space. The practical background of ID is that often only meteorological information is available when analyzing (non-)occurrence of shallow landslides and, at the same time, it could be that precipitation information is a good proxy for both meteorological trigger and hydrological cause. Although applied in many case studies, this approach suffers from many false positives as well as limited physical process understanding. Some first steps towards a more hydrologically based approach have been proposed in the past, but these efforts received limited follow-up.Therefore, the objective of our paper is to (a) critically analyze the concept of precipitation ID thresholds for shallow landslides and debris flows from a hydro-meteorological point of view and (b) propose a trigger-cause conceptual framework for lumped regional hydro-meteorological hazard assessment based on published examples and associated discussion. We discuss the ID thresholds in relation to return periods of precipitation, soil physics, and slope and catchment water balance. With this paper, we aim to contribute to the development of a stronger conceptual model for regional landslide hazard assessment based on physical process understanding and empirical data.

  5. Hydrometeorological threshold conditions for debris flow initiation in Norway

    Directory of Open Access Journals (Sweden)

    N. K. Meyer

    2012-10-01

    Full Text Available Debris flows, triggered by extreme precipitation events and rapid snow melt, cause considerable damage to the Norwegian infrastructure every year. To define intensity-duration (ID thresholds for debris flow initiation critical water supply conditions arising from intensive rainfall or snow melt were assessed on the basis of daily hydro-meteorological information for 502 documented debris flow events. Two threshold types were computed: one based on absolute ID relationships and one using ID relationships normalized by the local precipitation day normal (PDN. For each threshold type, minimum, medium and maximum threshold values were defined by fitting power law curves along the 10th, 50th and 90th percentiles of the data population. Depending on the duration of the event, the absolute threshold intensities needed for debris flow initiation vary between 15 and 107 mm day−1. Since the PDN changes locally, the normalized thresholds show spatial variations. Depending on location, duration and threshold level, the normalized threshold intensities vary between 6 and 250 mm day−1. The thresholds obtained were used for a frequency analysis of over-threshold events giving an estimation of the exceedance probability and thus potential for debris flow events in different parts of Norway. The absolute thresholds are most often exceeded along the west coast, while the normalized thresholds are most frequently exceeded on the west-facing slopes of the Norwegian mountain ranges. The minimum thresholds derived in this study are in the range of other thresholds obtained for regions with a climate comparable to Norway. Statistics reveal that the normalized threshold is more reliable than the absolute threshold as the former shows no spatial clustering of debris flows related to water supply events captured by the threshold.

  6. How, when, and for what reasons does land use modelling contribute to societal problem solving?

    NARCIS (Netherlands)

    Sterk, B.; Ittersum, van M.K.; Leeuwis, C.

    2011-01-01

    This paper reports and reflects on the contributions of land use models to societal problem solving. Its purpose is to inform model development and application and thus to increase chances for societal benefit of the modelling work. The key question is: How, when, and for what reasons does land use

  7. Research priorities in land use and land-cover change for the Earth System and Integrated Assessment Modelling

    NARCIS (Netherlands)

    Hibbard, K.; Janetos, A.; Vuuren, van D.; Pongratz, J.; Rose, S.; Betts, R.; Herold, M.; Feddema, J.

    2010-01-01

    This special issue has highlighted recent and innovative methods and results that integrate observations and modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated

  8. Time-varying parameter models for catchments with land use change: the importance of model structure

    Science.gov (United States)

    Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

    2018-05-01

    Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

  9. Time-varying parameter models for catchments with land use change: the importance of model structure

    Directory of Open Access Journals (Sweden)

    S. Pathiraja

    2018-05-01

    Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

  10. Land-Surface-Atmosphere Coupling in Observations and Models

    Directory of Open Access Journals (Sweden)

    Alan K Betts

    2009-07-01

    Full Text Available The diurnal cycle and the daily mean at the land-surface result from the coupling of many physical processes. The framework of this review is largely conceptual; looking for relationships and information in the coupling of processes in models and observations. Starting from the surface energy balance, the role of the surface and cloud albedos in the shortwave and longwave fluxes is discussed. A long-wave radiative scaling of the diurnal temperature range and the night-time boundary layer is summarized. Several aspects of the local surface energy partition are presented: the role of soilwater availability and clouds; vector methods for understanding mixed layer evolution, and the coupling between surface and boundary layer that determines the lifting condensation level. Moving to larger scales, evaporation-precipitation feedback in models is discussed; and the coupling of column water vapor, clouds and precipitation to vertical motion and moisture convergence over the Amazon. The final topic is a comparison of the ratio of surface shortwave cloud forcing to the diabatic precipitation forcing of the atmosphere in ERA-40 with observations.

  11. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  12. NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  13. Participatory Scenario Development to Address Potential Impacts of Land Use Change: An Example from the Italian Alps

    Directory of Open Access Journals (Sweden)

    Žiga Malek

    2015-05-01

    Full Text Available Changes to land use such as the removal of natural vegetation and expansion of urban areas can result in degradation of the landscape and an increase in hydro-meteorological risk. This has led to higher interest by decision-makers and scientists in the future consequences of these drivers. Scenario development can be a useful tool for addressing the high uncertainty regarding modeling future land use changes. Scenarios are not exact forecasts, but images of plausible futures. When studying future land dynamics, emphasis should be given to areas experiencing high rates of socioeconomic change. We have focused on the eastern Italian Alps, which face increasing pressure from tourism development. Identified drivers of local land use change are mostly external and difficult to quantify. This area, characterized by a traditional Alpine landscape, is subject to high levels of hydro-meteorological risk, another reason to study potential future land use changes. We tested a scenario generation method based on existing decisions and assumptions about future tourism development. We aimed to develop a framework leading to plausible scenarios that can overcome data inaccessibility and address external drivers. We combined qualitative methods, such as stakeholder interviews and cognitive mapping, with geospatial methods, such as geographic information systems, geostatistics, and environmental modeling. We involved stakeholders from the beginning to support the steps of generating data, understanding the system of land use change, and developing a land use change model for scenario development. In this way, we generated spatio-temporal scenarios that can assist future spatial planning and improve preparedness for possible undesirable development.

  14. A Framework for Modelling Indirect Land Use Changes in Life Cycle Assessment

    DEFF Research Database (Denmark)

    Schmidt, Jannick Højrup; Weidema, Bo Pedersen; Brandão, Miguel

    2015-01-01

    Around 9% of global CO2 emissions originate from land use changes. Often, these emissions are not appropriately addressed in Life Cycle Assessment. The link between demand for crops in one region and impacts in other regions is referred to here as indirect land use change (iLUC) and includes...... demand for land and land use changes is established through markets for land's production capacity. The iLUC model presented is generally applicable to all land use types, crops and regions of the world in typical LCA decision-making contexts focusing on the long-term effects of small-scale changes...... deforestation, intensification and reduced consumption. Existing models for iLUC tend to ignore intensification and reduced consumption, they most often operate with arbitrary amortisation periods to allocate deforestation emissions over time, and the causal link between land occupation and deforestation...

  15. Accounting for heterogeneity of public lands in hedonic property models

    Science.gov (United States)

    Charlotte Ham; Patricia A. Champ; John B. Loomis; Robin M. Reich

    2012-01-01

    Open space lands, national forests in particular, are usually treated as homogeneous entities in hedonic price studies. Failure to account for the heterogeneous nature of public open spaces may result in inappropriate inferences about the benefits of proximate location to such lands. In this study the hedonic price method is used to estimate the marginal values for...

  16. A large set of potential past, present and future hydro-meteorological time series for the UK

    Directory of Open Access Journals (Sweden)

    B. P. Guillod

    2018-01-01

    Full Text Available Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM driven by observed or projected sea surface temperature (SST and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM. Sets of 100 time series are generated for each of (i a historical baseline (1900–2006, (ii five near-future scenarios (2020–2049 and (iii five far-future scenarios (2070–2099. The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5 and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5 models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months and shorter-duration high precipitation (1–30 days, the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09 but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and

  17. A large set of potential past, present and future hydro-meteorological time series for the UK

    Science.gov (United States)

    Guillod, Benoit P.; Jones, Richard G.; Dadson, Simon J.; Coxon, Gemma; Bussi, Gianbattista; Freer, James; Kay, Alison L.; Massey, Neil R.; Sparrow, Sarah N.; Wallom, David C. H.; Allen, Myles R.; Hall, Jim W.

    2018-01-01

    Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five near-future scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions

  18. Radar-driven high-resolution hydro-meteorological forecasts of the 26 September 2007 Venice flash flood

    Science.gov (United States)

    Rossa, Andrea M.; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

    2010-11-01

    SummaryThis study aims to assess the feasibility of assimilating carefully checked radar rainfall estimates into a numerical weather prediction (NWP) to extend the forecasting lead time for an extreme flash flood. The hydro-meteorological modeling chain includes the convection-permitting NWP model COSMO-2 and a coupled hydrological-hydraulic model. Radar rainfall estimates are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood which impacted the coastal area of North-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the 90 km2 Dese river basin draining to the Venice Lagoon. The radar rainfall observations are carefully checked for artifacts, including rain-induced signal attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar rainfall estimates in the assimilation cycle of the NWP model is very significant. The main individual organized convective systems are successfully introduced into the model state, both in terms of timing and localization. Also, high-intensity incorrectly localized precipitation is correctly reduced to about the observed levels. On the other hand, the highest rainfall intensities computed after assimilation underestimate the observed values by 20% and 50% at a scale of 20 km and 5 km, respectively. The positive impact of assimilating radar rainfall estimates is carried over into the free forecast for about 2-5 h, depending on when the forecast was started. The positive impact is larger when the main mesoscale convective system is present in the initial conditions. The improvements in the precipitation forecasts are propagated to the river flow simulations, with an extension of the forecasting lead time up to 3 h.

  19. Identification and diagnosis of spatiotemporal hydrometeorological structure of heavy precipitation induced floods in Southeast Asia

    Science.gov (United States)

    Lu, M.; Hao, X.; Devineni, N.

    2017-12-01

    Extreme floods have a long history of being an important cause of death and destruction worldwide. It is estimated by Munich RE and Swiss RE that floods and severe storms dominate all other natural hazards globally in terms of average annual property loss and human fatalities. The top 5 most disastrous floods in the period from 1900 to 2015, ranked by economic damage, are all in the Asian monsoon region. This study presents an interdisciplinary approach integrating hydrometeorology, atmospheric science and state-of-the-art space-time statistics and modeling to investigate the association between the space-time characteristics of floods, precipitation and atmospheric moisture transport in a statistical and physical framework, using tropical moisture export dataset and curve clustering algorithm to study the source-to-destination features; explore the teleconnected climate regulations on the moisture formation process at different timescales (PDO, ENSO and MJO), and study the role of the synoptic-to-large atmospheric steering on the moisture transport and convergence.

  20. Analysis of impacts on hydrometeorological extremes in the Senegal River Basin from REMO RCM

    Energy Technology Data Exchange (ETDEWEB)

    Galiano, Sandra Garcia; Osorio, Juan Diego Giraldo [Technical Univ. of Cartagena, Dept. of Thermal Engineering and Fluids, Cartagena (Spain)

    2010-06-15

    West Africa is highly vulnerable to climate variability. The precipitation latitudinal gradient determines agricultural activities. The cultivated area of the Sahel is a densely populated region, whereas flood recession agriculture is practiced in the Senegal River Valley. The present study analyses both spatial-temporal rainfall patterns of the REMO Regional Climate Model (RCM) and observed rainfall data, focusing in particular on extreme hydro-meteorological phenomena. An analysis of simulated daily rainfall data was performed to determine the frequency and magnitude of length of dry spells, as well as the extreme rainfall events. A projected annual decrease in rainfall on horizon 2050 could be explained by two factors: the decrease in the percentage of rainy days on both west and north sides of the basin, and the decrease of precipitation amount for rainy days in the southern basin. Finally, an increase in the frequency of dry spell in the monsoon season by 2050 is projected. Such findings are significant in a framework of strategies for water resources management and planning at basin scale, in order to build adaptive capacity. (orig.)

  1. Modelling of cadmium fluxes on energy crop land

    International Nuclear Information System (INIS)

    Palm, V.

    1992-04-01

    The flux of cadmium on energy crop land is investigated. Three mechanisms are accounted for; Uptake by plant, transport with water, and sorption to soil. Sorption is described with Freundlich isotherms. The system is simulated mathematically in order to estimate the sensitivity and importance of different parameters on the cadmium flow and sorption. The water flux through the soil and the uptake by plants are simulated with a hydrological model, SOIL. The simulated time period is two years. The parameters describing root distribution and evaporation due to crop are taken from measurements on energy crop (Salix). The resulting water flux, water content in the soil profile and the water uptake into roots, for each day and soil compartment, are used in the cadmium sorption simulation. In the cadmium sorption simulation the flux and equilibrium chemistry of cadmium is calculated. It is shown that the amount of cadmium that accumulates in the plant, and the depth to which the applied cadmium reaches depends strongly on the constants in the sorption isotherm. With an application of 10 mg Cd/m 2 in the given range of Freundlich equations, the simulations gave a plant uptake of between 0 and 30 % of the applied cadmium in two years. At higher concentrations, where cadmium sorption can be described by nonlinear isotherms, more cadmium is present in soil water and is generally more bioavailable. 25 refs

  2. A Conceptual Model for Delineating Land Management Units (LMUs Using Geographical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Deniz Gerçek

    2017-06-01

    Full Text Available Land management and planning is crucial for present and future use of land and the sustainability of land resources. Physical, biological and cultural characteristics of land can be used to define Land Management Units (LMUs that aid in decision making for managing land and communicating information between different research and application domains. This study aims to describe the classification of ecologically relevant land units that are suitable for land management, planning and conservation purposes. Relying on the idea of strong correlation between landform and potential landcover, a conceptual model for creating Land Management Units (LMUs from topographic data and biophysical information is presented. The proposed method employs a multi-level object-based classification of Digital Terrain Models (DTMs to derive landform units. The sensitivity of landform units to changes in segmentation scale is examined, and the outcome of the landform classification is evaluated. Landform classes are then aggregated with landcover information to produce ecologically relevant landform/landcover assemblages. These conceptual units that constitute a framework of connected entities are finally enriched given available socio-economic information e.g., land use, ownership, protection status, etc. to generate LMUs. LMUs attached to a geographic database enable the retrieval of information at various levels to support decision making for land management at various scales. LMUs that are created present a basis for conservation and management in a biodiverse area in the Black Sea region of Turkey.

  3. Prediction of Land Use Change Based on Markov and GM(1,1 Models

    Directory of Open Access Journals (Sweden)

    SUN Yi-yang

    2016-05-01

    Full Text Available In order to explore the law of land use change in Laiwu City, Markov and GM(1,1 were respectively employed in the prediction of land use change in Laiwu from 2015 to 2050, after which the results were analyzed and discussed. The results showed that:(1The variational trends of all kinds of land use change predicted by the two models were consistent and the goodness of fit of the predictive value in corresponding years in the near future was high, illustrating that the predicted results in the near future were credible and the trend predicted in mid long term could be used as reference. (2The cultivated land would remanin almost no change from 2015 to 2020, and then gradually decreaseed in a small range from 2020 to 2050. The garden, the woodland, the grassland always reducing and the decreare range of the grassland was the largest. The urban village and industrial and mining land, the transportation land would be continuously increased and the range of urban village and industrial and mining land was the largest. The water and water conservancy facilities land and the other land would be always reduced in a very small range. It could be concluded that the results predicted by the two models in the near future were credible and could provide scientific basis for land use planning of Laiwu, while the method could provide reference for the prediction of land use change.

  4. Modeling the Dynamic Interrelations between Mobility, Utility, and Land Asking Price

    Science.gov (United States)

    Hidayat, E.; Rudiarto, I.; Siegert, F.; Vries, W. D.

    2018-02-01

    Limited and insufficient information about the dynamic interrelation among mobility, utility, and land price is the main reason to conduct this research. Several studies, with several approaches, and several variables have been conducted so far in order to model the land price. However, most of these models appear to generate primarily static land prices. Thus, a research is required to compare, design, and validate different models which calculate and/or compare the inter-relational changes of mobility, utility, and land price. The applied method is a combination of analysis of literature review, expert interview, and statistical analysis. The result is newly improved mathematical model which have been validated and is suitable for the case study location. This improved model consists of 12 appropriate variables. This model can be implemented in the Salatiga city as the case study location in order to arrange better land use planning to mitigate the uncontrolled urban growth.

  5. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-06-01

    Full Text Available This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

  6. 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

    Science.gov (United States)

    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

  7. Land Use and Land Cover Changes under Climate Uncertainty: Modelling the Impacts on Hydropower Production in Western Africa

    Directory of Open Access Journals (Sweden)

    Salomon Obahoundje

    2017-01-01

    Full Text Available The Bui hydropower plant plays a vital role in the socio-economic development of Ghana. This paper attempt to explore the combined effects of climate-land use land cover change on power production using the (WEAP model: Water Evaluation and Planning system. The historical analysis of rainfall and stream flow variability showed that the annual coefficient of variation of rainfall and stream flow are, respectively, 8.6% and 60.85%. The stream flow varied greatly than the rainfall, due to land use land cover changes (LULC. In fact, the LULC analysis revealed important changes in vegetative areas and water bodies. The WEAP model evaluation showed that combined effects of LULC and climate change reduce water availability for all of demand sectors, including hydropower generation at the Bui hydropower plant. However, it was projected that Bui power production will increase by 40.7% and 24.93%, respectively, under wet and adaptation conditions, and decrease by 46% and 2.5%, respectively, under dry and current conditions. The wet condition is defined as an increase in rainfall by 14%, the dry condition as the decrease in rainfall by 15%; current account is business as usual, and the adaptation is as the efficient use of water for the period 2012–2040.

  8. Radiation monitoring network of the Slovak Hydrometeorological Institute

    International Nuclear Information System (INIS)

    Melicherova, T.

    2005-01-01

    In 2000 Centre of Partial monitoring system 'Radioactivity of environment' was established on Slovak Hydrometeorology Institute (SHMI). Radiation monitoring network is one part of Radiation monitoring network of the Slovak Republic. At present SHMI operates in its monitoring network 23 detectors GammaTracer fy Genitron, one mobile detector and one stan by detector. All active detectors are placed in the professional meteorological stations in the selected parts of Slovakia. First one of these detectors was installed in 1999 and they replaced former type of detector (FAG). Last two detectors were installed in 2002. Detector GammaTracer has range of measurement from 20 nSv/h to 10 Sv/h. The detectors are calibrated every 2 years in the Slovak Institute of Metrology in compliance with the calibration plan. SHMI operates 4 aerosol monitors in Hurbanovo, Lucenec, Stropkov and Liesek. Filter 8 from these monitors are analysed in the Institute of Public Health (Cs-137, Be-7). On the base of bilateral agreement between the Austrian Ministry of Agriculture, Forestry, Environment and Water-Management and the Slovak Ministry of Environment Austrian side gave into the ownership of the Slovak side an automatic aerosol monitor AMS-02 including container and weather station. This monitor was installed in meteorological station Jaslovske Bohunice on 4-th October 2001. The Slovak Ministry of Environment provides the Austrian Ministry of Agriculture, Forestry, Environment and Water-Management with the readings of this monitor, free of charge, for at least 3 years and vice versa, the Austrian side gives the readings of the Austrian aerosol monitors to the Slovak Ministry of Environment free of charge. At present national monitoring center in Bratislava-Koliba is connected via ISDN line with Jaslovske Bohunice and Austrian center providing the data exchange. Radiation data (dose rate in the unit nSv/h) are collected via the Institute network to the MSS (message switch system) in the

  9. Evaluation of Intensive Construction Land Use in the Emerging City Based on PSR-Entropy model

    Science.gov (United States)

    Jia, Yuanyuan; Lei, Guangyu

    2018-01-01

    A comprehensive understanding of emerging city land utilization and the evaluation of intensive land use in the Emerging City will provide the comprehensive and reliable technical basis for the planning and management. It is an important node. According to the Han cheng from 2008 to 2016 years of land use, based on PSR-Entropy model of land use evaluation system, using entropy method to determine the index weight, the introduction of comprehensive index method to evaluate the degree of land use. The results show that the intensive land use comprehensive evaluation index of Han cheng increased from 2008 to 2015, but the land intensive use can not achieve the standards. The potential of further enhancing space is relatively large.

  10. Investigating the climate and carbon cycle impacts of CMIP6 Land Use and Land Cover Change in the Community Earth System Model (CESM2)

    Science.gov (United States)

    Lawrence, P.; Lawrence, D. M.; O'Neill, B. C.; Hurtt, G. C.

    2017-12-01

    For the next round of CMIP6 climate simulations there are new historical and SSP - RCP land use and land cover change (LULCC) data sets that have been compiled through the Land Use Model Intercomparison Project (LUMIP). The new time series data include new functionality following lessons learned through CMIP5 project and include new developments in the Community Land Model (CLM5) that will be used in all the CESM2 simulations of CMIP6. These changes include representing explicit crop modeling and better forest representation through the extended to 12 land units of the Global Land Model (GLM). To include this new information in CESM2 and CLM5 simulations new transient land surface data sets have been generated for the historical period 1850 - 2015 and for preliminary SSP - RCP paired future scenarios. The new data sets use updated MODIS Land Cover, Vegetation Continuous Fields, Leaf Area Index and Albedo to describe Primary and Secondary, Forested and Non Forested land units, as well as Rangelands and Pasture. Current day crop distributions are taken from the MIRCA2000 crop data set as done with the CLM 4.5 crop model and used to guide historical and future crop distributions. Preliminary "land only" simulations with CLM5 have been performed for the historical period and for the SSP1-RCP2.6 and SSP3-RCP7 land use and land cover change time series data. Equivalent no land use and land cover change simulations have been run for these periods under the same meteorological forcing data. The "land only" simulations use GSWP3 historical atmospheric forcing data from 1850 to 2010 and then time increasing RCP 8.5 atmospheric CO2 and climate anomalies on top of the current day GSWP3 atmospheric forcing data from 2011 to 2100. The offline simulations provide a basis to evaluate the surface climate, carbon cycle and crop production impacts of changing land use and land cover for each of these periods. To further evaluate the impacts of the new CLM5 model and the CMIP6 land

  11. Challenges and opportunities in land surface modelling of savanna ecosystems

    Directory of Open Access Journals (Sweden)

    R. Whitley

    2017-10-01

    Full Text Available The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs, which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model

  12. Immediate effects of modified landing pattern on a probabilistic tibial stress fracture model in runners.

    Science.gov (United States)

    Chen, T L; An, W W; Chan, Z Y S; Au, I P H; Zhang, Z H; Cheung, R T H

    2016-03-01

    Tibial stress fracture is a common injury in runners. This condition has been associated with increased impact loading. Since vertical loading rates are related to the landing pattern, many heelstrike runners attempt to modify their footfalls for a lower risk of tibial stress fracture. Such effect of modified landing pattern remains unknown. This study examined the immediate effects of landing pattern modification on the probability of tibial stress fracture. Fourteen experienced heelstrike runners ran on an instrumented treadmill and they were given augmented feedback for landing pattern switch. We measured their running kinematics and kinetics during different landing patterns. Ankle joint contact force and peak tibial strains were estimated using computational models. We used an established mathematical model to determine the effect of landing pattern on stress fracture probability. Heelstrike runners experienced greater impact loading immediately after landing pattern switch (Ptibial strains and the risk of tibial stress fracture in runners with different landing patterns (P>0.986). Immediate transitioning of the landing pattern in heelstrike runners may not offer timely protection against tibial stress fracture, despite a reduction of impact loading. Long-term effects of landing pattern switch remains unknown. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Comparison of two perturbation methods to estimate the land surface modeling uncertainty

    Science.gov (United States)

    Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

    2007-12-01

    In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

  14. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  15. Looking Forward: Using Scenario Modeling to Support Regional Land Use Planning in Northern Yukon, Canada

    Directory of Open Access Journals (Sweden)

    Shawn R. Francis

    2011-12-01

    We describe how the ALCES® landscape cumulative effects simulation model was used to explore possible outcomes of an oil and gas scenario in the Eagle Plain basin of the North Yukon Planning Region of Yukon Territory, Canada. Scenario modeling was conducted to facilitate informed discussion about key land use issues and practices, potential levels of landscape change, and possible socioeconomic benefits and environmental impacts. Modeling results supported the sustainable development and cumulative effects management recommendations of the North Yukon Regional Land Use Plan. Land use scenario modeling, as applied in this project, was found to be an effective approach for establishing sustainable development guidelines through a regional planning process.

  16. The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

    Science.gov (United States)

    Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

    2012-10-01

    Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

  17. The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

    Directory of Open Access Journals (Sweden)

    F. Souty

    2012-10-01

    Full Text Available Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii a spatially explicit distribution of potential (maximal crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL. The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

  18. Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

    Science.gov (United States)

    Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

    2013-04-01

    The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of

  19. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

    Science.gov (United States)

    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

  20. Multiregional input-output model for China's farm land and water use.

    Science.gov (United States)

    Guo, Shan; Shen, Geoffrey Qiping

    2015-01-06

    Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.

  1. Modelling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera

    Science.gov (United States)

    Kusratmoko, E.; Albertus, S. D. Y.; Supriatna

    2017-01-01

    This research has a purpose to study and develop a model that can representing and simulating spatial distribution pattern of land use change in Komering watershed. The Komering watershed is one of nine sub Musi river basin and is located in the southern part of Sumatra island that has an area of 8060,62 km2. Land use change simulations, achieved through Markov-cellular automata (CA) methodologies. Slope, elevation, distance from road, distance from river, distance from capital sub-district, distance from settlement area area were driving factors that used in this research. Land use prediction result in 2030 also shows decrease of forest acreage up to -3.37%, agricultural land decreased up to -2.13%, and open land decreased up to -0.13%. On the other hand settlement area increased up to 0.07%, and plantation land increased up to 5.56%. Based on the predictive result, land use unconformity percentage to RTRW in Komering watershed is 18.62 % and land use conformity is 58.27%. Based on the results of the scenario, where forest in protected areas and agriculture land are maintained, shows increase the land use conformity amounted to 60.41 % and reduce unconformity that occur in Komering watershed to 17.23 %.

  2. A window of opportunities : the contributions of land use modelling to societal learning

    NARCIS (Netherlands)

    Sterk, B.

    2007-01-01

    It has been argued that the management of land, whether at the field, farm or regional scale, can benefit from computer-based land use system analysis. As a result, a large number of computer-based models and tools have been produced over the past decades with the aim of providing support to policy

  3. An economic theory-based explanatory model of agricultural land-use patterns

    NARCIS (Netherlands)

    Diogo, V.; Koomen, E.; Kuhlman, T.

    2015-01-01

    An economic theory-based land-use modelling framework is presented aiming to explain the causal link between economic decisions and resulting spatial patterns of agricultural land use. The framework assumes that farmers pursue utility maximisation in agricultural production systems, while

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

    Science.gov (United States)

    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.

  5. Calibration and validation of land-use models

    NARCIS (Netherlands)

    Vliet, van J.

    2013-01-01

    Land use is constantly changing. For example, urban areas expand as a result of population growth, cropping patterns change to fulfil the demand for bioenergy and natural vegetation recovers in locations where farmers cease to farm. Understanding these changes is pivotal to explore future

  6. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

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

    Science.gov (United States)

    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.

  8. Scenario modelling of land use/land cover changes in Munessa-Shashemene landscape of the Ethiopian highlands.

    Science.gov (United States)

    Kindu, Mengistie; Schneider, Thomas; Döllerer, Martin; Teketay, Demel; Knoke, Thomas

    2018-05-01

    Models under a set of scenarios are used to simulate and improve our understanding of land use/land cover (LULC) changes, which is central for sustainable management of a given natural resource. In this study, we simulated and examined the possible future LULC patterns and changes in Munessa-Shashemene landscape of the Ethiopian highlands covering four decades (2012-2050) using a spatially explicit GIS-based model. Both primary and secondary sources were utilized to identify relevant explanatory variables (drivers) and LULC datasets for the model. Three alternative scenarios, namely Business As Usual (BAU), Forest Conservation and Water Protection (FCWP) and Sustainable Intensification (SI) were used. The simulated LULC map of 2012 was compared with the actual for model validation and showed a good consistency. The results revealed that areas of croplands will increase widely under the BAU scenario and would expand to the remaining woodlands, natural forests and grasslands, reflecting vulnerability of these LULC types and potential loss of associated ecosystem service values (ESVs). FCWP scenario would bring competition among other LULC types, particularly more pressure to the grassland ecosystem. Hence, the two scenarios will result in severe LULC dynamics that lead to serious environmental crisis. The SI scenario, with holistic approach, demonstrated that expansion of croplands could vigorously be reduced, remaining forests better conserved and degraded land recovered, resulting in gains of the associated total ESVs. We conclude that a holistic landscape management, i.e. SI, is the best approach to ensure expected production while safeguarding the environment of the studied landscape and elsewhere with similar geographic settings. Further study is suggested to practically test our framework through a research for development approach in a test site so that it can be used as a model area for effective use and conservation of our natural resources. Copyright

  9. Biofuels and Land Use Change: Applying Recent Evidence to Model Estimates

    Directory of Open Access Journals (Sweden)

    Wallace E. Tyner

    2013-01-01

    Full Text Available Biofuels impact on global land use has been a controversial yet important topic. Up until recently, there has not been enough biofuels to have caused major land use change, so the evidence from actual global land use data has been scant. However, in the past decade, there have been 72 million hectares added to global crop cover. In this research we take advantage of this new data to calibrate the Global Trade Analysis Project (GTAP model and parameters. We make two major changes. First, we calibrate the land transformation parameters (called constant elasticity of transformation, CET to global regions so that the parameters better reflect the actual land cover change that has occurred. Second, we alter the land cover nesting structure. In the old GTAP model, cropland, pasture, and forest were all in the same nest suggesting, everything else being equal, that pasture or forest convert to cropland with equal ease and cost. However, we now take advantage of the fact that pasture converts to cropland at lower cost than forest. The paper provides the theoretical and empirical justification for these two model improvements. Then it re-evaluates the global land use impacts due to the USA ethanol program using the improved model tuned with actual observations. Finally, it shows that compared to the old model, the new model projects: (1 less expansion in global cropland due to ethanol expansion; (2 lower U.S. share in global cropland expansion; (3 and lower forest share in global cropland expansion.

  10. A Framework for the Land Use Change Dynamics Model Compatible with RCMs

    Directory of Open Access Journals (Sweden)

    Xiangzheng Deng

    2013-01-01

    Full Text Available A framework of land use change dynamics (LUCD model compatible with regional climate models (RCMs is introduced in this paper. The LUCD model can be subdivided into three modules, namely, economic module, vegetation change module, and agent-based module. The economic module is capable of estimating the demand of land use changes in economic activities maximizing economic utility. A computable general equilibrium (CGE modeling framework is introduced and an approach to introduce land as a production factor into the economic module is proposed. The vegetation change module provides the probability of vegetation change driven by climate change. The agroecological zone (AEZ model is supposed to be the optimal option for constructing the vegetation change module. The agent-based module identifies whether the land use change demand and vegetation change can be realized and provides the land use change simulation results which are the underlying surfaces needed by RCM. By importing the RCMs' simulation results of climate change and providing the simulation results of land use change for RCMs, the LUCD model would be compatible with RCMs. The coupled simulation system composed of LUCD and RCMs can be very effective in simulating the land surface processes and their changing patterns.

  11. Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

    KAUST Repository

    Zampieri, Matteo

    2012-02-01

    Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model - CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river-groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale. © 2011 Elsevier B.V.

  12. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Directory of Open Access Journals (Sweden)

    F. Fundel

    2013-01-01

    Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.

    The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive

  13. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2013-01-01

    Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

  14. Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

    Science.gov (United States)

    Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H

    2016-12-01

    Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC

  15. Modelling Interactions between Land Use, Climate, and Hydrology along with Stakeholders’ Negotiation for Water Resources Management

    Directory of Open Access Journals (Sweden)

    Babak Farjad

    2017-11-01

    Full Text Available This paper describes the main functionalities of an integrated framework to model the interactions between land use, climate, and hydrology along with stakeholders’ negotiation. Its novelty lies in the combination of individual-based and spatially distributed models within the Socio-Hydrology paradigm to capture the complexity and uncertainty inherent to these systems. It encompasses a land-use/land-cover cellular automata model, an agent-based model used for automated stakeholders’ negotiation, and the hydrological MIKE SHE/MIKE 11 model, which are linked and can be accessed through a web-based interface. It enables users to run simulations to explore a wide range of scenarios related to land development and water resource management while considering the reciprocal influence of human and natural systems. This framework was developed with the involvement of key stakeholders from the initial design stage to the final demonstration and validation.

  16. ANALYSIS OF LAND RESOURCES SUITABILITY BY FUNCTIONAL MODEL IN EASTERN CROATIA REGION

    Directory of Open Access Journals (Sweden)

    Vladimir Vukadinović

    2011-06-01

    Full Text Available A total of 17405 soil samples (2003rd-2009th years were analyzed in the eastern part of Croatia. The aim of this paper is to assess land suitability for crops i.e. to describe quantitatively land quality and indicate disadvantages of land using system in investigated area. The described mathematical model uses score functions for estimating indicators of soil suitability. Soil suitability assessment computer model for crops, supported by GIS, proved to be fast, efficient and enough reliable. Using GIS tool it is possible to visualize land suitability and present it in different cartographic bases such as maps whereas using geostatistical method – kriging enables to possible to provide regionalization of production area based on quantitative assessment of land suitability for crops.

  17. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  18. Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

    Science.gov (United States)

    Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

    2016-01-01

    The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

  19. Land use change and prediction in the Baimahe Basin using GIS and CA-Markov model

    International Nuclear Information System (INIS)

    Wang, Shixu; Zhang, Zulu; Wang, Xue

    2014-01-01

    Using ArcGIS and IDRISI, land use dynamics and Shannon entropy information were applied in this paper to analyze the quantity and structure change in the Baimahe Basin from 1996 to 2008. A CA-Markov model was applied to predict the land use patterns in 2020. Results showed that farmland, forest and construction land are the dominant land use types in the Baimahe Basin. From 1996 to 2008, areas of farmland and forest decreased and other land use types increased, with construction land increasing the most. The prediction results showed that the changes in land use patterns from 2008 to 2020 would be the same with those from 1996 to 2008. Main changes are the transiting out of farmland and forest and the transiting in of construction land. The order degree of the whole basin goes on decreasing. Measures of farmland protection and grain for green projects should be adopted to enhance the stability of land use system in the Baimahe Basin in order to promote regional sustainable development

  20. Land-Use Change Modelling in the Upper Blue Nile Basin

    Directory of Open Access Journals (Sweden)

    Seleshi G. Yalew

    2016-08-01

    Full Text Available Land-use and land-cover changes are driving unprecedented changes in ecosystems and environmental processes at different scales. This study was aimed at identifying the potential land-use drivers in the Jedeb catchment of the Abbay basin by combining statistical analysis, field investigation and remote sensing. To do so, a land-use change model was calibrated and evaluated using the SITE (SImulation of Terrestrial Environment modelling framework. SITE is cellular automata based multi-criteria decision analysis framework for simulating land-use conversion based on socio-economic and environmental factors. Past land-use trajectories (1986–2009 were evaluated using a reference Landsat-derived map (agreement of 84%. Results show that major land-use change drivers in the study area were population, slope, livestock and distances from various infrastructures (roads, markets and water. It was also found that farmers seem to increasingly prefer plantations of trees such as Eucalyptus by replacing croplands perhaps mainly due to declining crop yield, soil fertility and climate variability. Potential future trajectory of land-use change was also predicted under a business-as-usual scenario (2009–2025. Results show that agricultural land will continue to expand from 69.5% in 2009 to 77.5% in 2025 in the catchment albeit at a declining rate when compared with the period from 1986 to 2009. Plantation forest will also increase at a much higher rate, mainly at the expense of natural vegetation, agricultural land and grasslands. This study provides critical information to land-use planners and policy makers for a more effective and proactive management in this highland catchment.

  1. Bayesian spatial modelling and the significance of agricultural land use to scrub typhus infection in Taiwan.

    Science.gov (United States)

    Wardrop, Nicola A; Kuo, Chi-Chien; Wang, Hsi-Chieh; Clements, Archie C A; Lee, Pei-Fen; Atkinson, Peter M

    2013-11-01

    Scrub typhus is transmitted by the larval stage of trombiculid mites. Environmental factors, including land cover and land use, are known to influence breeding and survival of trombiculid mites and, thus, also the spatial heterogeneity of scrub typhus risk. Here, a spatially autoregressive modelling framework was applied to scrub typhus incidence data from Taiwan, covering the period 2003 to 2011, to provide increased understanding of the spatial pattern of scrub typhus risk and the environmental and socioeconomic factors contributing to this pattern. A clear spatial pattern in scrub typhus incidence was observed within Taiwan, and incidence was found to be significantly correlated with several land cover classes, temperature, elevation, normalized difference vegetation index, rainfall, population density, average income and the proportion of the population that work in agriculture. The final multivariate regression model included statistically significant correlations between scrub typhus incidence and average income (negatively correlated), the proportion of land that contained mosaics of cropland and vegetation (positively correlated) and elevation (positively correlated). These results highlight the importance of land cover on scrub typhus incidence: mosaics of cropland and vegetation represent a transitional land cover type which can provide favourable habitats for rodents and, therefore, trombiculid mites. In Taiwan, these transitional land cover areas tend to occur in less populated and mountainous areas, following the frontier establishment and subsequent partial abandonment of agricultural cultivation, due to demographic and socioeconomic changes. Future land use policy decision-making should ensure that potential public health outcomes, such as modified risk of scrub typhus, are considered.

  2. A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

    Science.gov (United States)

    Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

    2015-01-01

    A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

  3. Procedural modeling of urban layout: population, land use, and road network

    OpenAIRE

    Lyu, X.; Han, Q.; de Vries, B.

    2017-01-01

    This paper introduces an urban simulation system generating urban layouts with population, road network and land use layers. The desired urban spatial structure is obtained by generating a population map based on population density models. The road network is generated at two spatial levels corresponding to the road hierarchy. The land use allocation is based on the What If? allocation model. The expected results are urban layouts suitable for academic scenario analysis.

  4. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-01-01

    Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

  5. LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description

    Science.gov (United States)

    Schaphoff, Sibyll; von Bloh, Werner; Rammig, Anja; Thonicke, Kirsten; Biemans, Hester; Forkel, Matthias; Gerten, Dieter; Heinke, Jens; Jägermeyr, Jonas; Knauer, Jürgen; Langerwisch, Fanny; Lucht, Wolfgang; Müller, Christoph; Rolinski, Susanne; Waha, Katharina

    2018-04-01

    This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL" target="_blank">https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

  6. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

    OpenAIRE

    Bateman, Ian; Agarwala, M.; Binner, A.; Coombes, E.; Day, B.; Ferrini, Silvia; Fezzi, C.; Hutchins, M.; Lovett, A.; Posen, P.

    2016-01-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact...

  7. Integrated modelling and the impacts of water management on land use

    International Nuclear Information System (INIS)

    Dorner, W; Spachinger, K; Metzka, R

    2008-01-01

    River systems and the quantity and quality of water depend on the catchment, its structure and land use. In central Europe especially land is a scarce resource. This causes conflicts between different types of land use, but also with the interests of flood protection, nature conservation and the protection of water resources and water bodies in the flood plain and on a catchment scale. ILUP - Integrated Land Use Planning and River Basin Management was a project, funded by the European Union, to address the problems of conflicting interests within a catchment. It addressed the problems of conflicting land use from a hydrological perspective and with regard to the resulting problems of water management. Two test river basins, Vils and Rott, both with a catchment size of about 1000 square kilometres, were considered for the German part of the project. Objective of the project was to identify means of managing land use with regard to water management objectives and adapt planning strategies and methodologies of water management authorities to the new needs of catchment management and planning. Catchment models were derived to simulate hydrological processes, assess the safety of dams and improve the control strategy of detention reservoirs with regard to land use in the lower system. Hydrodynamic models provided the basis to assess flood prone areas, evaluate flood protection measures and analyze the impacts of river training and discharge on morphology. Erosion and transport models were used to assess the impacts of land use on water quality. Maps were compiled from model results to provide a basis for decision making. In test areas new ways of planning and implementation of measures were tested. As a result of model scenarios in combination with the socio economic situation in the catchment new methods of land management and land use management were derived and implemented in model areas. The results of the project show that new ways of managing land use in river

  8. The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

    Science.gov (United States)

    Forney, William M.; Oldham, I. Benson; Crescenti, Neil

    2013-01-01

    This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include

  9. Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

    Science.gov (United States)

    Chilukoti, N.; Xue, Y.

    2016-12-01

    The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

  10. The trends of modeling the ways of formation, distribution and exploitation of megapolis lands using geo-information systems

    Directory of Open Access Journals (Sweden)

    Kostyantyn Mamonov

    2017-10-01

    Full Text Available The areas of need for ways of modeling the formation, distribution and use of land metropolis using GIS are identified. The article is to define the areas of modeling ways of formation, distribution and use of land metropolis using GIS. In the study, the following objectives are set: to develop an algorithm process data base (Data System creation for pecuniary valuation of land settlements with the use of GIS; to offer process model taking into account the influence of one factor modules using geographic information systems; to identify components of geo providing expert money evaluation of land metropolis; to describe the general procedure for expert money assessment of land and property by using geographic information system software; to develop an algorithm methods for expert evaluation of land. Identified tools built algorithms used for modeling the ways of formation, distribution and use of land metropolis using GIS. Directions ways of modeling the formation, distribution and use of land metropolis using GIS.

  11. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-05-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks.

  12. Modeling the Behaviour of an Advanced Material Based Smart Landing Gear System for Aerospace Vehicles

    International Nuclear Information System (INIS)

    Varughese, Byji; Dayananda, G. N.; Rao, M. Subba

    2008-01-01

    The last two decades have seen a substantial rise in the use of advanced materials such as polymer composites for aerospace structural applications. In more recent years there has been a concerted effort to integrate materials, which mimic biological functions (referred to as smart materials) with polymeric composites. Prominent among smart materials are shape memory alloys, which possess both actuating and sensory functions that can be realized simultaneously. The proper characterization and modeling of advanced and smart materials holds the key to the design and development of efficient smart devices/systems. This paper focuses on the material characterization; modeling and validation of the model in relation to the development of a Shape Memory Alloy (SMA) based smart landing gear (with high energy dissipation features) for a semi rigid radio controlled airship (RC-blimp). The Super Elastic (SE) SMA element is configured in such a way that it is forced into a tensile mode of high elastic deformation. The smart landing gear comprises of a landing beam, an arch and a super elastic Nickel-Titanium (Ni-Ti) SMA element. The landing gear is primarily made of polymer carbon composites, which possess high specific stiffness and high specific strength compared to conventional materials, and are therefore ideally suited for the design and development of an efficient skid landing gear system with good energy dissipation characteristics. The development of the smart landing gear in relation to a conventional metal landing gear design is also dealt with

  13. Model studies of crosswind landing-gear configurations for STOL aircraft

    Science.gov (United States)

    Stubbs, S. M.; Byrdsong, T. A.

    1973-01-01

    A dynamic model was used to directly compare four different crosswind landing gear mechanisms. The model was landed as a free body onto a laterally sloping runway used to simulate a crosswind side force. A radio control system was used for steering to oppose the side force as the model rolled to a stop. The configuration in which the landing gears are alined by the pilot and locked in the direction of motion prior to touchdown gave the smoothest runout behavior with the vehicle maintaining its crab angle throughout the landing roll. Nose wheel steering was confirmed to be better than steering with nose and main gears differentially or together. Testing is continuing to obtain quantitative data to establish an experimental data base for validation of an analytical program that will be capable of predicting full scale results.

  14. Challenges in land model representation of heat transfer in snow and frozen soils

    Science.gov (United States)

    Musselman, K. N.; Clark, M. P.; Nijssen, B.; Arnold, J.

    2017-12-01

    Accurate model simulations of soil thermal and moisture states are critical for realistic estimates of exchanges of energy, water, and biogeochemical fluxes at the land-atmosphere interface. In cold regions, seasonal snow-cover and organic soils form insulating barriers, modifying the heat and moisture exchange that would otherwise occur between mineral soils and the atmosphere. The thermal properties of these media are highly dynamic functions of mass, water and ice content. Land surface models vary in their representation of snow and soil processes, and thus in the treatment of insulation and heat exchange. For some models, recent development efforts have improved representation of heat transfer in cold regions, such as with multi-layer snow treatment, inclusion of soil freezing and organic soil properties, yet model deficiencies remain prevalent. We evaluate models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) experiment for proficiency in simulating heat transfer between the soil through the snowpack to the atmosphere. Using soil observations from cold region sites and a controlled experiment with Structure for Unifying Multiple Modeling Alternatives (SUMMA), we explore the impact of snow and soil model decisions and parameter values on heat transfer model skill. Specifically, we use SUMMA to mimic the spread of behaviors exhibited by the models that participated in PLUMBER. The experiment allows us to isolate relationships between model skill and process representation. The results are aimed to better understand existing model challenges and identify potential advances for cold region models.

  15. Analysis and Modeling of Urban Land Cover Change in Setúbal and Sesimbra, Portugal

    Directory of Open Access Journals (Sweden)

    Yikalo H. Araya

    2010-06-01

    Full Text Available The expansion of cities entails the abandonment of forest and agricultural lands, and these lands’ conversion into urban areas, which results in substantial impacts on ecosystems. Monitoring these changes and planning urban development can be successfully achieved using multitemporal remotely sensed data, spatial metrics, and modeling. In this paper, urban land use change analysis and modeling was carried out for the Concelhos of Setúbal and Sesimbra in Portugal. An existing land cover map for the year 1990, together with two derived land cover maps from multispectral satellite images for the years 2000 and 2006, were utilized using an object-oriented classification approach. Classification accuracy assessment revealed satisfactory results that fulfilled minimum standard accuracy levels. Urban land use dynamics, in terms of both patterns and quantities, were studied using selected landscape metrics and the Shannon Entropy index. Results show that urban areas increased by 91.11% between 1990 and 2006. In contrast, the change was only 6.34% between 2000 and 2006. The entropy value was 0.73 for both municipalities in 1990, indicating a high rate of urban sprawl in the area. In 2006, this value, for both Sesimbra and Setúbal, reached almost 0.90. This is demonstrative of a tendency toward intensive urban sprawl. Urban land use change for the year 2020 was modeled using a Cellular Automata based approach. The predictive power of the model was successfully validated using Kappa variations. Projected land cover changes show a growing tendency in urban land use, which might threaten areas that are currently reserved for natural parks and agricultural lands.

  16. Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

    Science.gov (United States)

    Manukalo, V.

    2012-12-01

    Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of

  17. Evaluation of Landing Characteristics Achieved by Simulations and Flight Tests on a Small-scaled Model Related to Magnetically Levitated Advanced Take-off and Landing Operations

    NARCIS (Netherlands)

    Rohacs, D.; Voskuijl, M.; Siepenkotter, N.

    2014-01-01

    The goal of this paper is to simulate and measure on a small-scaled model the landing characteristics related to take-off and landing (TOL) operations supported by a magnetic levitation (MAGLEV) system as ground-based power supply. The technical feasibility and the potential benefits of using

  18. Data mining and model adaptation for the land use and land cover classification of a Worldview 2 image

    Science.gov (United States)

    Nascimento, L. C.; Cruz, C. B. M.; Souza, E. M. F. R.

    2013-10-01

    Forest fragmentation studies have increased since the last 3 decades. Land use and land cover maps (LULC) are important tools for this analysis, as well as other remote sensing techniques. The object oriented analysis classifies the image according to patterns as texture, color, shape, and context. However, there are many attributes to be analyzed, and data mining tools helped us to learn about them and to choose the best ones. In this way, the aim of this paper is to describe data mining techniques and results of a heterogeneous area, as the municipality of Silva Jardim, Rio de Janeiro, Brazil. The municipality has forest, urban areas, pastures, water bodies, agriculture and also some shadows as objects to be represented. Worldview 2 satellite image from 2010 was used and LULC classification was processed using the values that data mining software has provided according to the J48 method. Afterwards, this classification was analyzed, and the verification was made by the confusion matrix, being possible to evaluate the accuracy (58,89%). The best results were in classes "water" and "forest" which have more homogenous reflectance. Because of that, the model has been adapted, in order to create a model for the most homogeneous classes. As result, 2 new classes were created, some values and some attributes changed, and others added. In the end, the accuracy was 89,33%. It is important to highlight this is not a conclusive paper; there are still many steps to develop in highly heterogeneous surfaces.

  19. Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

    Science.gov (United States)

    Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

    2016-12-01

    State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

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

    Science.gov (United States)

    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.

  1. Coupling integrated assessment and earth system models: concepts and an application to land use change

    Science.gov (United States)

    O'Neill, B. C.; Lawrence, P.; Ren, X.

    2016-12-01

    Collaboration between the integrated assessment modeling (IAM) and earth system modeling (ESM) communities is increasing, driven by a growing interest in research questions that require analysis integrating both social and natural science components. This collaboration often takes the form of integrating their respective models. There are a number of approaches available to implement this integration, ranging from one-way linkages to full two-way coupling, as well as approaches that retain a single modeling framework but improve the representation of processes from the other framework. We discuss the pros and cons of these different approaches and the conditions under which a two-way coupling of IAMs and ESMs would be favored over a one-way linkage. We propose a criterion that is necessary and sufficient to motivate two-way coupling: A human process must have an effect on an earth system process that is large enough to cause a change in the original human process that is substantial compared to other uncertainties in the problem being investigated. We then illustrate a test of this criterion for land use-climate interactions based on work using the Community Earth System Model (CESM) and land use scenarios from the Representative Concentration Pathways (RCPs), in which we find that the land use effect on regional climate is unlikely to meet the criterion. We then show an example of implementing a one-way linkage of land use and agriculture between an IAM, the integrated Population-Economy-Technology-Science (iPETS) model, and CESM that produces fully consistent outcomes between iPETS and the CESM land surface model. We use the linked system to model the influence of climate change on crop yields, agricultural land use, crop prices and food consumption under two alternative future climate scenarios. This application demonstrates the ability to link an IAM to a global land surface and climate model in a computationally efficient manner.

  2. A stochastic Forest Fire Model for future land cover scenarios assessment

    Directory of Open Access Journals (Sweden)

    M. D'Andrea

    2010-10-01

    Full Text Available 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.

  3. The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

    Science.gov (United States)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand; hide

    2016-01-01

    The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in fluxtower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation forwhy land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.

  4. Towards systematic evaluation of crop model outputs for global land-use models

    Science.gov (United States)

    Leclere, David; Azevedo, Ligia B.; Skalský, Rastislav; Balkovič, Juraj; Havlík, Petr

    2016-04-01

    Land provides vital socioeconomic resources to the society, however at the cost of large environmental degradations. Global integrated models combining high resolution global gridded crop models (GGCMs) and global economic models (GEMs) are increasingly being used to inform sustainable solution for agricultural land-use. However, little effort has yet been done to evaluate and compare the accuracy of GGCM outputs. In addition, GGCM datasets require a large amount of parameters whose values and their variability across space are weakly constrained: increasing the accuracy of such dataset has a very high computing cost. Innovative evaluation methods are required both to ground credibility to the global integrated models, and to allow efficient parameter specification of GGCMs. We propose an evaluation strategy for GGCM datasets in the perspective of use in GEMs, illustrated with preliminary results from a novel dataset (the Hypercube) generated by the EPIC GGCM and used in the GLOBIOM land use GEM to inform on present-day crop yield, water and nutrient input needs for 16 crops x 15 management intensities, at a spatial resolution of 5 arc-minutes. We adopt the following principle: evaluation should provide a transparent diagnosis of model adequacy for its intended use. We briefly describe how the Hypercube data is generated and how it articulates with GLOBIOM in order to transparently identify the performances to be evaluated, as well as the main assumptions and data processing involved. Expected performances include adequately representing the sub-national heterogeneity in crop yield and input needs: i) in space, ii) across crop species, and iii) across management intensities. We will present and discuss measures of these expected performances and weight the relative contribution of crop model, input data and data processing steps in performances. We will also compare obtained yield gaps and main yield-limiting factors against the M3 dataset. Next steps include

  5. Land-use change trajectories up to 2050: insights from a global agro-economic model comparison

    NARCIS (Netherlands)

    Schmitz, C.; Meijl, van J.C.M.; Kyle, P.; Nelson, G.C.; Fujimori, S.; Gurgel, A.; Havlik, P.; Heyhoe, E.; Mason d'Croz, D.; Popp, A.; Sands, R.; Tabeau, A.A.; Mensbrugghe, van der D.; Lampe, von M.; Wise, M.; Blanc, E.; Hasegawa, T.; Kavallari, A.; Valin, H.

    2014-01-01

    Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land-use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive

  6. GLDAS Noah Land Surface Model L4 3 Hourly 1.0 x 1.0 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  7. An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

    Science.gov (United States)

    Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue

    2013-10-15

    Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Modeling the fate and transport of bacteria in agricultural and pasture lands using APEX

    Science.gov (United States)

    The Agricultural Policy/Environmental eXtender (APEX) model is a whole farm to small watershed scale continuous simulation model developed for evaluating various land management strategies. The current version, APEX0806, does not have the modeling capacity for fecal indicator bacteria fate and trans...

  9. Calibration of a distributed hydrology and land surface model using energy flux measurements

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Refsgaard, Jens Christian; Jensen, Karsten H.

    2016-01-01

    In this study we develop and test a calibration approach on a spatially distributed groundwater-surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measure...

  10. Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

    Science.gov (United States)

    Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

    2017-09-01

    With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  11. Selecting locations for landing of various formations of helicopters using spatial modelling

    International Nuclear Information System (INIS)

    Kovarik, V; Rybansky, M

    2014-01-01

    During crisis situations such as floods, landslides, humanitarian crisis and even military clashes there are situations when it is necessary to send helicopters to the crisis areas. To facilitate the process of searching for the sites suitable for landing, it is possible to use the tools of spatial modelling. The paper describes a procedure of selecting areas potentially suitable for landing of particular formations of helicopters. It lists natural and man-made terrain features that represent the obstacles that can prevent helicopters from landing. It also states specific requirements of the NATO documents that have to be respected when selecting the areas for landing. These requirements relate to a slope of ground and an obstruction angle on approach and exit paths. Creating the knowledge base and graphical models in ERDAS IMAGINE is then described. In the first step of the procedure the areas generally suitable for landing are selected. Then the different configurations of landing points that form the landing sites are created and corresponding outputs are generated. Finally, several tactical requirements are incorporated

  12. Impact of land use change on the land atmosphere carbon flux of South and South East Asia: A Synthesis of Dynamic Vegetation Model Results

    Science.gov (United States)

    Cervarich, M.; Shu, S.; Jain, A. K.; Poulter, B.; Stocker, B.; Arneth, A.; Viovy, N.; Kato, E.; Wiltshire, A.; Koven, C.; Sitch, S.; Zeng, N.; Friedlingstein, P.

    2015-12-01

    Understanding our present day carbon cycle and possible solutions to recent increases in atmospheric carbon dioxide is dependent upon quantifying the terrestrial carbon budget. Currently, global land cover and land use change is estimated to emit 0.9 PgC yr-1 compared to emissions due to fossil fuel combustion and cement production of 8.4 PgC yr-1. South and Southeast Asia (India, Nepal, Bhutan, Bangladesh, Burma, Thailand, Laos, Vietnam, Cambodia, Malaysia, Philippines, Indonesia, Pakistan, Myanmar, and Singapore) is a region of rapid land cover and land use change due to the continuous development of agriculture, deforestation, reforestation, afforestation, and the increased demand of land for people to live. In this study, we synthesize outputs of nine models participated in Global Carbon Budget Project to identify the carbon budget of South and southeast Asia, diagnose the contribution of land cover and land use change to carbon emissions and assess areas of uncertainty in the suite of models. Uncertainty is determined using the standard deviation and the coefficient of variation of net ecosystem exchange and its component parts. Results show the region's terrestrial biosphere was a source of carbon emissions from the 1980 to the early 1990s. During the same time period, land cover and land use change increasingly contributed to carbon emission. In the most recent two decades, the region became a carbon sink since emission due to land cover land use changes. Spatially, the greatest total emissions occurred in the tropical forest of Southeast Asia. Additionally, this is the subregion with the greatest uncertainty and greatest biomass. Model uncertainty is shown to be proportional to total biomass. The atmospheric impacts of ENSO are shown to suppress the net biosphere productivity in South and Southeast Asia leading to years of increased carbon emissions.

  13. Comparison of regional and global land cover products and the implications for biogenic emission modeling.

    Science.gov (United States)

    Huang, Ling; McDonald-Buller, Elena; McGaughey, Gary; Kimura, Yosuke; Allen, David T

    2015-10-01

    Accurate estimates of biogenic emissions are required for air quality models that support the development of air quality management plans and attainment demonstrations. Land cover characterization is an essential driving input for most biogenic emissions models. This work contrasted the global Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product against a regional land cover product developed for the Texas Commissions on Environmental Quality (TCEQ) over four climate regions in eastern Texas, where biogenic emissions comprise a large fraction of the total inventory of volatile organic compounds (VOCs) and land cover is highly diverse. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was utilized to investigate the influences of land cover characterization on modeled isoprene and monoterpene emissions through changes in the standard emission potential and emission activity factor, both separately and simultaneously. In Central Texas, forest coverage was significantly lower in the MODIS land cover product relative to the TCEQ data, which resulted in substantially lower estimates of isoprene and monoterpene emissions by as much as 90%. Differences in predicted isoprene and monoterpene emissions associated with variability in land cover characterization were primarily caused by differences in the standard emission potential, which is dependent on plant functional type. Photochemical modeling was conducted to investigate the effects of differences in estimated biogenic emissions associated with land cover characterization on predicted ozone concentrations using the Comprehensive Air Quality Model with Extensions (CAMx). Mean differences in maximum daily average 8-hour (MDA8) ozone concentrations were 2 to 6 ppb with maximum differences exceeding 20 ppb. Continued focus should be on reducing uncertainties in the representation of land cover through field validation. Uncertainties in the estimation of biogenic emissions associated with

  14. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-02-01

    The increase in irrigated agriculture in Saudi Arabia is having a large impact on its limited groundwater resources. While large-scale water storage changes can be estimated using satellite data, monitoring groundwater abstraction rates is largely non-existent at either farm or regional level, so water management decisions remain ill-informed. Although determining water use from space at high spatiotemporal resolutions remains challenging, a number of approaches have shown promise, particularly in the retrieval of crop water use via evaporation. Apart from satellite-based estimates, land surface models offer a continuous spatial-temporal evolution of full land-atmosphere water and energy exchanges. In this study, we first examine recent trends in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight into the challenges of evaporation retrieval in arid environments. Finally, we present a novel method aimed to retrieve groundwater abstraction rates used in irrigated fields by constraining a land surface model with remote sensing-based evaporation observations. The approach is used to reproduce reported irrigation rates over 41 center-pivot irrigation fields presenting a range of crop dynamics over the course of one year. The results of this application are promising, with mean absolute errors below 3 mm:day-1, bias of -1.6 mm:day-1, and a first rough estimate of total annual abstractions of 65.8 Mm3 (close to the estimated value using reported farm data, 69.42 Mm3). However, further efforts to address the overestimation of bare soil evaporation in the model are required. The uneven coverage of satellite data within the study site allowed us to evaluate its impact on the optimization, with a better match between observed and obtained irrigation rates on fields with

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

    Science.gov (United States)

    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.

  16. A Comparison of Vacancy Dynamics between Growing and Shrinking Cities Using the Land Transformation Model

    Directory of Open Access Journals (Sweden)

    Jaekyung Lee

    2018-05-01

    Full Text Available Every city seeks opportunities to spur economic developments and, depending on its type, vacant land can be seen as a potential threat or an opportunity to achieve these developments. Although vacant land exists in all cities, the causes and effects of changes in vacant land can differ. Growing cities may have more vacant land than shrinking cities because of large scale annexation. Meanwhile, depopulation and economic downturn may increase the total amount of vacant and abandoned properties. Despite various causes of increase and decrease of vacant land, the ability to predict future vacancy patterns—where future vacant parcels may occur—could be a critical test to set up appropriate development strategies and land use policies, especially in shrinking cities, to manage urban decline and regeneration efforts more wisely. This study compares current and future vacancy patterns of a growing city (Fort Worth, TX, USA and a shrinking city (Chicago, IL, USA, by employing the Land Transformation Model (LTM to predict for future vacant lands. This research predicts and produces possible vacancy pattern scenarios by 2020 and deciphers the ranking of determinants of vacant land in each city type. The outcomes of this study indicate that the LTM can be useful for simulating vacancy patterns and the causes of vacancy vary in both growing and shrinking cities. Socio-economic factors such as unemployment rate and household income are powerful determinants of vacancy in a growing city, while physical and transportation-related conditions such as proximity to highways, vehicle accessibility, or building conditions show a stronger influence on increasing vacant land in a shrinking city.

  17. Multi-scale, multi-model assessment of projected land allocation

    Science.gov (United States)

    Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.

    2017-12-01

    Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the

  18. Modeling salt movement and halophytic crop growth on marginal lands with the APEX model

    Science.gov (United States)

    Goehring, N.; Saito, L.; Verburg, P.; Jeong, J.; Garrett, A.

    2016-12-01

    Saline soils negatively impact crop productivity in nearly 20% of irrigated agricultural lands worldwide. At these saline sites, cultivation of highly salt-tolerant plants, known as halophytes, may increase productivity compared to conventional salt-sensitive crops (i.e., glycophytes), thereby increasing the economic potential of marginal lands. Through a variety of mechanisms, halophytes are more effective than glycophytes at excluding, accumulating, and secreting salts from their tissues. Each mechanism can have a different impact on the salt balance in the plant-soil-water system. To date, little information is available to understand the long-term impacts of halophyte cultivation on environmental quality. This project utilizes the Agricultural Policy/Environmental Extender (APEX) model, developed by the US Department of Agriculture, to model the growth and production of two halophytic crops. The crops being modeled include quinoa (Chenopodium quinoa), which has utilities for human consumption and forage, and AC Saltlander green wheatgrass (Elymus hoffmannii), which has forage utility. APEX simulates salt movement between soil layers and accounts for the salt balance in the plant-soil-water system, including salinity in irrigation water and crop-specific salt uptake. Key crop growth parameters in APEX are derived from experimental growth data obtained under non-stressed conditions. Data from greenhouse and field experiments in which quinoa and AC Saltlander were grown under various soil salinity and irrigation salinity treatments are being used to parameterize, calibrate, and test the model. This presentation will discuss progress on crop parameterization and completed model runs under different salt-affected soil and irrigation conditions.

  19. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-08-01

    Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled

  20. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  1. Developing an Agent-Based Model to Simulate Urban Land-Use Expansion (Case Study: Qazvin)

    OpenAIRE

    F. Nourian; A. A. Alesheikh; F. Hosseinali

    2012-01-01

    Extended abstract1-IntroductionUrban land-use expansion is a challenging issue in developing countries. Increases in population as well as the immigration from the villages to the cities are the two major factors for that phenomenon. Those factors have reduced the influence of efforts that try to limit the cities’ boundaries. Thus, spatial planners always look for the models that simulate the expansion of urban land-uses and enable them to prevent unbalanced expansions of cities and guide the...

  2. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    CSIR Research Space (South Africa)

    Marshall, M

    2013-03-01

    Full Text Available , latent energy (LE: ET energy equivalent) during the rainy season is the primary regulator after solar forcing of energy balance seasonal variability, the strength of which changes signifi- cantly across land cover types (Ramier et al., 2009). At inter... Table 1. Acronyms and their definitions in order of appearance. Acronym Definition ET Evapotranspiration LE Latent Heat LSM Land Surface Model NDVI Normalized Difference Vegetation Index PET Potential Evapotranspiration AMMA African Monsoon...

  3. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  4. State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales

    NARCIS (Netherlands)

    Wang, T.; Brender, P.; Ciais, P.; Piao, S.; Mahecha, M.D.; Chevallier, F.; Reichstein, M.; Ottle, C.; Maignan, F.; Arain, A.; Bohrer, G.; Cescatti, A.; Kiely, G.; Law, B.E.; Lutz, M.; Montagnani, L.; Moors, E.J.

    2012-01-01

    Characterization of state-dependent model biases in land surface models can highlight model deficiencies, and provide new insights into model development. In this study, artificial neural networks (ANNs) are used to estimate the state-dependent biases of a land surface model (ORCHIDEE: ORganising

  5. Participatory Evaluation of Monitoring and Modeling of Sustainable Land Management Technologies in Areas Prone to Land Degradation

    Science.gov (United States)

    Stringer, L. C.; Fleskens, L.; Reed, M. S.; de Vente, J.; Zengin, M.

    2014-11-01

    Examples of sustainable land management (SLM) exist throughout the world. In many cases, SLM has largely evolved through local traditional practices and incremental experimentation rather than being adopted on the basis of scientific evidence. This means that SLM technologies are often only adopted across small areas. The DESIRE (DESertIfication mitigation and REmediation of degraded land) project combined local traditional knowledge on SLM with empirical evaluation of SLM technologies. The purpose of this was to evaluate and select options for dissemination in 16 sites across 12 countries. It involved (i) an initial workshop to evaluate stakeholder priorities (reported elsewhere), (ii) field trials/empirical modeling, and then, (iii) further stakeholder evaluation workshops. This paper focuses on workshops in which stakeholders evaluated the performance of SLM technologies based on the scientific monitoring and modeling results from 15 study sites. It analyses workshop outcomes to evaluate how scientific results affected stakeholders' perceptions of local SLM technologies. It also assessed the potential of this participatory approach in facilitating wider acceptance and implementation of SLM. In several sites, stakeholder preferences for SLM technologies changed as a consequence of empirical measurements and modeling assessments of each technology. Two workshop examples are presented in depth to: (a) explore the scientific results that triggered stakeholders to change their views; and (b) discuss stakeholders' suggestions on how the adoption of SLM technologies could be up-scaled. The overall multi-stakeholder participatory approach taken is then evaluated. It is concluded that to facilitate broad-scale adoption of SLM technologies, de-contextualized, scientific generalisations must be given local context; scientific findings must be viewed alongside traditional beliefs and both scrutinized with equal rigor; and the knowledge of all kinds of experts must be

  6. Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K; Zhang, H

    2005-12-01

    This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and

  7. An Approach for Calculating Land Valuation by Using Inspire Data Models

    Science.gov (United States)

    Aydinoglu, A. C.; Bovkir, R.

    2017-11-01

    Land valuation is a highly important concept for societies and governments have always emphasis on the process especially for taxation, expropriation, market capitalization and economic activity purposes. To success an interoperable and standardised land valuation, INSPIRE data models can be very practical and effective. If data used in land valuation process produced in compliance with INSPIRE specifications, a reliable and effective land valuation process can be performed. In this study, possibility of the performing land valuation process with using the INSPIRE data models was analysed and with the help of Geographic Information Systems (GIS) a case study in Pendik was implemented. For this purpose, firstly data analysis and gathering was performed. After, different data structures were transformed according to the INSPIRE data model requirements. For each data set necessary ETL (Extract-Transform-Load) tools were produced and all data transformed according to the target data requirements. With the availability and practicability of spatial analysis tools of GIS software, land valuation calculations were performed for study area.

  8. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    International Nuclear Information System (INIS)

    Ter Maat, H.W.; Hutjes, R.W.A.; Miglietta, F.; Gioli, B.; Bosveld, F.C.; Vermeulen, A.T.; Fritsch, H.

    2010-08-01

    This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables.

  9. Soil mapping and processes modelling for sustainable land management: a review

    Science.gov (United States)

    Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

    2017-04-01

    Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B

  10. Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

    Science.gov (United States)

    Kraus, P. M.; Denning, S.

    2015-12-01

    The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced

  11. Documentary evidence of economic character as a source for the study of hydrometeorological extremes

    Science.gov (United States)

    Chromá, K.; Brázdil, R.; Valášek, H.

    2009-04-01

    Various human activities, such as agriculture, forestry and water management, have always been influenced by climate variability and hydrometeorological extremes. From this reason historical economic records often include information about contemporaneous weather as well as descriptions of its impacts. This study deals with the interpretation of hydrometeorological extremes for the territory of Moravia (eastern part of the Czech Republic) derived from taxation records and reports of domain and estate administrators. Information obtained reflects the occurrence of floods, convective storms (including hailstorms), windstorms, late spring and early autumn frosts. Based on data from eight domains or estates, frequency series of floods and convective storms (including hailstorms) were compiled for the period 1650-1849. Detail analysis of disastrous weather event from 10 August 1694 in the Pernštejn domain is used to demonstrate the potential of such data for the study of hydrometeorological extremes and their impacts on human activity. Another example is analysis of data about tax reduction due to hailstorm damage on agriculture crops in Moravia in the period 1896-1906.

  12. 2016 International Land Model Benchmarking (ILAMB) Workshop Report

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Koven, Charles D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Keppel-Aleks, Gretchen [Univ. of Michigan, Ann Arbor, MI (United States); Lawrence, David M. [National Center for Atmospheric Research, Boulder, CO (United States); Riley, William J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Randerson, James T. [Univ. of California, Irvine, CA (United States); Ahlström, Anders [Stanford Univ., Stanford, CA (United States); Lund Univ., Lund (Sweden); Abramowitz, Gabriel [Univ. of New South Wales, Sydney, NSW (Australia); Baldocchi, Dennis D. [Univ. of California, Berkeley, CA (United States); Best, Martin J. [UK Met Office, Exeter, EX1 3PB (United Kingdom); Bond-Lamberty, Benjamin [Joint Global Change Research Institute, Pacific Northwest National Lab. (PNNL), College Park, MD (United States); De Kauwe, Martin G. [Macquarie Univ., NSW (Australia); Denning, A. Scott [Colorado State Univ., Fort Collins, CO (United States); Desai, Ankur R. [Univ. of Wisconsin, Madison, WI (United States); Eyring, Veronika [Deutsches Zentrum fuer Luft- und Raumfahrt (DLR), Oberpfaffenhofen (Germany); Fisher, Joshua B. [California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.; Fisher, Rosie A. [National Center for Atmospheric Research, Boulder, CO (United States); Gleckler, Peter J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Huang, Maoyi [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hugelius, Gustaf [Stockholm Univ. (Sweden); Jain, Atul K. [Univ. of Illinois, Urbana, IL (United States); Kiang, Nancy Y. [NASA Goddard Institute for Space Studies, Columbia Univ., New York, NY (United States); Kim, Hyungjum [University of Tokyo, Bunkyo-ku, Tokyo (Japan); Koster, Randal D. [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Kumar, Sujay V. [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Li, Hongyi [Tsinghua Univ., Beijing (China). Dept. of Hydraulic Engineering; Luo, Yiqi [Univ. of Oklahoma, Norman, OK (United States); Mao, Jiafu [Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States); McDowell, Nathan G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mishra, Umakant [Argonne National Lab. (ANL), Argonne, IL (United States); Moorcroft, Paul R. [Harvard Univ., Cambridge, MA (United States); Pau, George S.H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ricciuto, Daniel M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schaefer, Kevin [Univ. of Colorado, Boulder, CO (United States). National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences; Schwalm, Christopher R. [Woods Hole Research Center, Falmouth, MA (United States); Serbin, Shawn P. [Brookhaven National Lab. (BNL), Upton, NY (United States); Shevliakova, Elena [Geophysical Fluid Dynamics Laboratory, Princeton Univ., Princeton, NJ (United States); Slater, Andrew G. [Univ. of Colorado, Boulder, CO (United States). National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences; Tang, Jinyun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Mathew [Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences and NERC National Centre for Earth Observation; Xia, Jianyang [Univ. of Oklahoma, Norman, OK (United States); East China Normal Univ. (ECNU), Shanghai (China). Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences; Xu, Chonggang [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Joseph, Renu [US Department of Energy, Germantown, MD (United States); Koch, Dorothy [US Department of Energy, Germantown, MD (United States)

    2017-04-01

    As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

  13. 2016 International Land Model Benchmarking (ILAMB) Workshop Report

    Science.gov (United States)

    Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.; hide

    2016-01-01

    As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.

  14. LPJmL4 - a dynamic global vegetation model with managed land - Part 2: Model evaluation

    Science.gov (United States)

    Schaphoff, Sibyll; Forkel, Matthias; Müller, Christoph; Knauer, Jürgen; von Bloh, Werner; Gerten, Dieter; Jägermeyr, Jonas; Lucht, Wolfgang; Rammig, Anja; Thonicke, Kirsten; Waha, Katharina

    2018-04-01

    The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through https://gitlab.pik-potsdam.de/lpjml/LPJmL" target="_blank">https://gitlab.pik-potsdam.de/lpjml/LPJmL. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.

  15. Sustainability of integrated land and water resources management in the face of climate and land use changes

    Science.gov (United States)

    Setegn, Shimelis

    2017-04-01

    Sustainable development integrates economic development, social development, and environmental protection. Land and Water resources are under severe pressure from increasing populations, fast development, deforestation, intensification of agriculture and the degrading environment in many part of the world. The demand for adequate and safe supplies of water is becoming crucial especially in the overpopulated urban centers of the Caribbean islands. Moreover, population growth coupled with environmental degradation and possible adverse impacts of land use and climate change are major factors limiting freshwater resource availability. The main objective of this study is to develop a hydrological model and analyze the spatiotemporal variability of hydrological processes in the Caribbean islands of Puerto Rico and Jamaica. Physically based eco-hydrological model was developed and calibrated in the Rio Grande Manati and Wag water watershed. Spatial distribution of annual hydrological processes, water balance components for wet and dry years, and annual hydrological water balance of the watershed are discussed. The impact of land use and climate change are addressed in the watersheds. Appropriate nature based adaptation strategies were evaluated. The study will present a good understanding of advantages and disadvantages of nature-based solutions for adapting climate change, hydro-meteorological risks and other extreme hydrological events.

  16. Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

    Science.gov (United States)

    Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

    2015-04-01

    Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

  17. Land cover change impact on urban flood modeling (case study: Upper Citarum watershed)

    Science.gov (United States)

    Siregar, R. I.

    2018-03-01

    The upper Citarum River watershed utilizes remote sensing technology in Geographic Information System to provide information on land coverage by interpretation of objects in the image. Rivers that pass through urban areas will cause flooding problems causing disadvantages, and it disrupts community activities in the urban area. Increased development in a city is related to an increase in the number of population growth that added by increasing quality and quantity of life necessities. Improved urban lifestyle changes have an impact on land cover. The impact in over time will be difficult to control. This study aims to analyze the condition of flooding in urban areas caused by upper Citarum watershed land-use change in 2001 with the land cover change in 2010. This modeling analyzes with the help of HEC-RAS to describe flooded inundation urban areas. Land cover change in upper Citarum watershed is not very significant; it based on the results of data processing of land cover has the difference of area that changed is not enormous. Land cover changes for the floods increased dramatically to a flow coefficient for 2001 is 0.65 and in 2010 at 0.69. In 2001, the inundation area about 105,468 hectares and it were about 92,289 hectares in 2010.

  18. Using 3d Bim Model for the Value-Based Land Share Calculations

    Science.gov (United States)

    Çelik Şimşek, N.; Uzun, B.

    2017-11-01

    According to the Turkish condominium ownership system, 3D physical buildings and its condominium units are registered to the condominium ownership books via 2D survey plans. Currently, 2D representations of the 3D physical objects, causes inaccurate and deficient implementations for the determination of the land shares. Condominium ownership and easement right are established with a clear indication of land shares (condominium ownership law, article no. 3). So, the land share of each condominium unit have to be determined including the value differences among the condominium units. However the main problem is that, land share has often been determined with area based over the project before construction of the building. The objective of this study is proposing a new approach in terms of value-based land share calculations of the condominium units that subject to condominium ownership. So, the current approaches and its failure that have taken into account in determining the land shares are examined. And factors that affect the values of the condominium units are determined according to the legal decisions. This study shows that 3D BIM models can provide important approaches for the valuation problems in the determination of the land shares.

  19. Modeling Net Land Occupation of Hydropower Reservoirs in Norway for Use in Life Cycle Assessment.

    Science.gov (United States)

    Dorber, Martin; May, Roel; Verones, Francesca

    2018-02-20

    Increasing hydropower electricity production constitutes a unique opportunity to mitigate climate change impacts. However, hydropower electricity production also impacts aquatic and terrestrial biodiversity through freshwater habitat alteration, water quality degradation, and land use and land use change (LULUC). Today, no operational model exists that covers any of these cause-effect pathways within life cycle assessment (LCA). This paper contributes to the assessment of LULUC impacts of hydropower electricity production in Norway in LCA. We quantified the inundated land area associated with 107 hydropower reservoirs with remote sensing data and related it to yearly electricity production. Therewith, we calculated an average net land occupation of 0.027 m 2 ·yr/kWh of Norwegian storage hydropower plants for the life cycle inventory. Further, we calculated an adjusted average land occupation of 0.007 m 2 ·yr/kWh, accounting for an underestimation of water area in the performed maximum likelihood classification. The calculated land occupation values are the basis to support the development of methods for assessing the land occupation impacts of hydropower on biodiversity in LCA at a damage level.

  20. Modelling Spatial Compositional Data: Reconstructions of past land cover and uncertainties

    DEFF Research Database (Denmark)

    Pirzamanbein, Behnaz; Lindström, Johan; Poska, Anneli

    2018-01-01

    In this paper, we construct a hierarchical model for spatial compositional data, which is used to reconstruct past land-cover compositions (in terms of coniferous forest, broadleaved forest, and unforested/open land) for five time periods during the past $6\\,000$ years over Europe. The model...... to a fast MCMC algorithm. Reconstructions are obtained by combining pollen-based estimates of vegetation cover at a limited number of locations with scenarios of past deforestation and output from a dynamic vegetation model. To evaluate uncertainties in the predictions a novel way of constructing joint...... confidence regions for the entire composition at each prediction location is proposed. The hierarchical model's ability to reconstruct past land cover is evaluated through cross validation for all time periods, and by comparing reconstructions for the recent past to a present day European forest map...

  1. Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

    Science.gov (United States)

    Xu, L.

    1994-01-01

    A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

  2. Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

    Science.gov (United States)

    Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

    2007-12-01

    Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

  3. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian

    2016-01-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared...... to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice...

  4. Land use transport interaction models: Application perspectives for the city of Thessaloniki

    Directory of Open Access Journals (Sweden)

    Pozoukidou Georgia

    2014-01-01

    Full Text Available Land use patterns and transport system are considered to be the two basic components of the urban development process, and as such they have been in the core of spatial planning policies for the last 4 decades. Land use transport interaction models are computer tools that could help us understand land use changes and organization of human activities in relation to existing or planned transport infrastructure. In this context this paper examines the perspectives of applying a land use transport interaction model for the city of Thessaloniki. Obtaining, preparing and validating socioeconomic data is a crucial part of the modeling process, therefore an extensive search of the required data was performed. The quest for appropriate and suitable data concluded with a detailed recording of emerged problems. In response to the inability of finding suitable data to perform the first step of the modeling process i.e. calibration, the paper concludes with some thoughts related to data availability, organization and standardization issues. Last but not least, the paper stresses out the significance of data availability for utilization of land use transport models, so as not to remain purely academic products but tools with practical value in planning.

  5. OPTIMIZATION OF LAND USE SUITABILITY FOR AGRICULTURE USING INTEGRATED GEOSPATIAL MODEL AND GENETIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    S. B. Mansor

    2012-08-01

    Full Text Available In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

  6. Refining multi-model projections of temperature extremes by evaluation against land-atmosphere coupling diagnostics

    Science.gov (United States)

    Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.

    2017-05-01

    The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land-atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T-ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T-ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected

  7. Improving weather predictability by including land-surface model parameter uncertainty

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

    The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

  8. Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5

    Directory of Open Access Journals (Sweden)

    D. Wang

    2017-07-01

    Full Text Available Land surface models bear substantial biases in simulating surface water and energy budgets despite the continuous development and improvement of model parameterizations. To reduce model biases, Parr et al. (2015 proposed a method incorporating satellite-based evapotranspiration (ET products into land surface models. Here we apply this bias correction method to the Community Land Model version 4.5 (CLM4.5 and test its performance over the conterminous US (CONUS. We first calibrate a relationship between the observational ET from the Global Land Evaporation Amsterdam Model (GLEAM product and the model ET from CLM4.5, and assume that this relationship holds beyond the calibration period. During the validation or application period, a simulation using the default CLM4.5 (CLM is conducted first, and its output is combined with the calibrated observational-vs.-model ET relationship to derive a corrected ET; an experiment (CLMET is then conducted in which the model-generated ET is overwritten with the corrected ET. Using the observations of ET, runoff, and soil moisture content as benchmarks, we demonstrate that CLMET greatly improves the hydrological simulations over most of the CONUS, and the improvement is stronger in the eastern CONUS than the western CONUS and is strongest over the Southeast CONUS. For any specific region, the degree of the improvement depends on whether the relationship between observational and model ET remains time-invariant (a fundamental hypothesis of the Parr et al. (2015 method and whether water is the limiting factor in places where ET is underestimated. While the bias correction method improves hydrological estimates without improving the physical parameterization of land surface models, results from this study do provide guidance for physically based model development effort.

  9. Recent Advances in Modeling of the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model

    Science.gov (United States)

    Advances in the land surface model (LSM) and planetary boundary layer (PBL) components of the WRF-CMAQ coupled meteorology and air quality modeling system are described. The aim of these modifications was primarily to improve the modeling of ground level concentrations of trace c...

  10. Estimating the impact of land use change on surface energy partition based on the Noah model

    Science.gov (United States)

    Chen, Shaohui; Su, Hongbo; Zhan, Jinyan

    2014-03-01

    It is well known that land use has an important impact on surface energy partition. It is important to study the evolving trend of the partition of sensible heat flux (SHF) and latent heat flux (LHF) from the net radiance (NR) with land use change in the context of regional climate changes. In this paper, we studied the response of energy partition to land use using the Noah model. First, the Noah model simulation results of SHF and LHF between 2003 and 2005 were comprehensively validated using the observation data from the Changbai Mountain Station, the Xilinhot Station, and the Yucheng Station. The study domains represent three different types of land use change: excessive deforestation, grassland degeneration aggravation, and groundwater level decline, respectively. The study period was subsequently extended from 2015 through 2034, using four projected land use maps and forcing data from Princeton (2000-2004). The simulation results show that during the land use conversions, the annual average of LHF drops by 10.7%, rises by 10.1%, and drops by 11.5% for the Changbai Mountain, Inner Mongolia, and Northern China stations, respectively while the annual average of SHF rises by 10.6%, drops by 10.1%, and drops by 11.3% for the three areas.

  11. Nonlinear modeling of adaptive magnetorheological landing gear dampers under impact conditions

    Science.gov (United States)

    Ahuré Powell, Louise A.; Choi, Young T.; Hu, Wei; Wereley, Norman M.

    2016-11-01

    Adaptive landing gear dampers that can continuously adjust their stroking load in response to various operating conditions have been investigated for improving the landing performance of a lightweight helicopter. In prior work, adaptive magnetorheological (MR) landing gear dampers that maintained a constant peak stroking force of 4000 lbf across sink rates ranging from 6 to 12 ft s-1 were designed, fabricated and successfully tested. In this follow-on effort, it is desired to expand the high end of the sink rate range to hold the peak stroking load constant for sink rates ranging from 6 to 26 ft s-1, thus extending the high end of the speed range from 12 (in the first study) to 26 ft s-1. To achieve this increase, a spring-based relief valve MR landing gear damper was developed. In order to better understand the MR landing gear damper behavior, a modified nonlinear Bingham Plastic model was formulated, and it incorporates Darcy friction, viscous forces across the MR and relief valves to better account for the damper force behavior at higher speeds. In addition, gas pressure inside the MR damper piston is considered so the total damper force includes a gas force. The MR landing gear damper performance is characterized using drop tests, and the experiments are used to validate model predictions data at low and high nominal impact speeds up to 26 ft s-1 (shaft velocity of 9.6 ft s-1).

  12. Bus Lifecycle Cost Model for Federal Land Management Agencies.

    Science.gov (United States)

    2011-09-30

    The Bus Lifecycle Cost Model is a spreadsheet-based planning tool that estimates capital, operating, and maintenance costs for various bus types over the full lifecycle of the vehicle. The model is based on a number of operating characteristics, incl...

  13. Optimization of land use of agricultural farms in Sumedang regency by using linear programming models

    Science.gov (United States)

    Zenis, F. M.; Supian, S.; Lesmana, E.

    2018-03-01

    Land is one of the most important assets for farmers in Sumedang Regency. Therefore, agricultural land should be used optimally. This study aims to obtain the optimal land use composition in order to obtain maximum income. The optimization method used in this research is Linear Programming Models. Based on the results of the analysis, the composition of land use for rice area of 135.314 hectares, corn area of 11.798 hectares, soy area of 2.290 hectares, and peanuts of 2.818 hectares with the value of farmers income of IDR 2.682.020.000.000,-/year. The results of this analysis can be used as a consideration in decisions making about cropping patterns by farmers.

  14. A hierarchical updating method for finite element model of airbag buffer system under landing impact

    Directory of Open Access Journals (Sweden)

    He Huan

    2015-12-01

    Full Text Available In this paper, we propose an impact finite element (FE model for an airbag landing buffer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence of the structure FE model from the full impact FE model to develop a hierarchical updating scheme for the recovery module FE model and the airbag system FE model. Second, we define impact responses at key points to compare the computational and experimental results to resolve the inconsistency between the experimental data sampling frequency and experimental triggering. To determine the typical characteristics of the impact dynamics response of the airbag landing buffer system, we present the impact response confidence factors (IRCFs to evaluate how consistent the computational and experiment results are. An error function is defined between the experimental and computational results at key points of the impact response (KPIR to serve as a modified objective function. A radial basis function (RBF is introduced to construct updating variables for a surrogate model for updating the objective function, thereby converting the FE model updating problem to a soluble optimization problem. Finally, the developed method has been validated using an experimental and computational study on the impact dynamics of a classic airbag landing buffer system.

  15. HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

    Science.gov (United States)

    GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

  16. GIS based generation of dynamic hydrological and land patch simulation models for rural watershed areas

    Directory of Open Access Journals (Sweden)

    M. Varga

    2016-03-01

    Full Text Available This paper introduces a GIS based methodology to generate dynamic process model for the simulation based analysis of a sensitive rural watershed. The Direct Computer Mapping (DCM based solution starts from GIS layers and, via the graph interpretation and graphical edition of the process network, the expert interface is able to integrate the field experts’ knowledge in the computer aided generation of the simulation model. The methodology was applied and tested for the Southern catchment basin of Lake Balaton, Hungary. In the simplified hydrological model the GIS description of nine watercourses, 121 water sections, 57 small lakes and 20 Lake Balaton compartments were mapped through the expert interface to the dynamic databases of the DCM model. The hydrological model involved precipitation, evaporation, transpiration, runoff, infiltration. The COoRdination of INformation on the Environment (CORINE land cover based simplified “land patch” model considered the effect of meteorological and hydrological scenarios on freshwater resources in the land patches, rivers and lakes. The first results show that the applied model generation methodology helps to build complex models, which, after validation can support the analysis of various land use, with the consideration of environmental aspects.

  17. Supporting Fiscal Aspect of Land Administration through an LADM-based Valuation Information Model

    NARCIS (Netherlands)

    Kara, A.; Çağdaş, V.; Lemmen, C.H.J.; Işıkdağ, Ü.; van Oosterom, P.J.M.; Stubkjær, E.

    2018-01-01

    This paper presents an information system artifact for the fiscal aspect of land administration, a valuation information model for the specification of inventories or databases used in valuation for recurrently levied immovable property taxes. The information model is designed as an extension module

  18. Implementation ambiguity: The fifth element long lost in uncertainty budgets for land biogeochemical modeling

    Science.gov (United States)

    Tang, J.; Riley, W. J.

    2015-12-01

    Previous studies have identified four major sources of predictive uncertainty in modeling land biogeochemical (BGC) processes: (1) imperfect initial conditions (e.g., assumption of preindustrial equilibrium); (2) imperfect boundary conditions (e.g., climate forcing data); (3) parameterization (type I equifinality); and (4) model structure (type II equifinality). As if that were not enough to cause substantial sleep loss in modelers, we propose here a fifth element of uncertainty that results from implementation ambiguity that occurs when the model's mathematical description is translated into computational code. We demonstrate the implementation ambiguity using the example of nitrogen down regulation, a necessary process in modeling carbon-climate feedbacks. We show that, depending on common land BGC model interpretations of the governing equations for mineral nitrogen, there are three different implementations of nitrogen down regulation. We coded these three implementations in the ACME land model (ALM), and explored how they lead to different preindustrial and contemporary land biogeochemical states and fluxes. We also show how this implementation ambiguity can lead to different carbon-climate feedback estimates across the RCP scenarios. We conclude by suggesting how to avoid such implementation ambiguity in ESM BGC models.

  19. Water balance versus land surface model in the simulation of Rhine river discharges

    NARCIS (Netherlands)

    Hurkmans, R.T.W.L.; Moel, de H.; Aerts, J.C.J.H.; Troch, P.A.

    2008-01-01

    Accurate streamflow simulations in large river basins are crucial to predict timing and magnitude of floods and droughts and to assess the hydrological impacts of climate change. Water balance models have been used frequently for these purposes. Compared to water balance models, however, land

  20. Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

    Science.gov (United States)

    Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

    2016-11-01

    With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

  1. Fishery landing forecasting using EMD-based least square support vector machine models

    Science.gov (United States)

    Shabri, Ani

    2015-05-01

    In this paper, the novel hybrid ensemble learning paradigm integrating ensemble empirical mode decomposition (EMD) and least square support machine (LSSVM) is proposed to improve the accuracy of fishery landing forecasting. This hybrid is formulated specifically to address in modeling fishery landing, which has high nonlinear, non-stationary and seasonality time series which can hardly be properly modelled and accurately forecasted by traditional statistical models. In the hybrid model, EMD is used to decompose original data into a finite and often small number of sub-series. The each sub-series is modeled and forecasted by a LSSVM model. Finally the forecast of fishery landing is obtained by aggregating all forecasting results of sub-series. To assess the effectiveness and predictability of EMD-LSSVM, monthly fishery landing record data from East Johor of Peninsular Malaysia, have been used as a case study. The result shows that proposed model yield better forecasts than Autoregressive Integrated Moving Average (ARIMA), LSSVM and EMD-ARIMA models on several criteria..

  2. Modeling of tropospheric NO2 column over different climatic zones and land use/land cover types in South Asia

    Science.gov (United States)

    ul-Haq, Zia; Rana, Asim Daud; Tariq, Salman; Mahmood, Khalid; Ali, Muhammad; Bashir, Iqra

    2018-03-01

    We have applied regression analyses for the modeling of tropospheric NO2 (tropo-NO2) as the function of anthropogenic nitrogen oxides (NOx) emissions, aerosol optical depth (AOD), and some important meteorological parameters such as temperature (Temp), precipitation (Preci), relative humidity (RH), wind speed (WS), cloud fraction (CLF) and outgoing long-wave radiation (OLR) over different climatic zones and land use/land cover types in South Asia during October 2004-December 2015. Simple linear regression shows that, over South Asia, tropo-NO2 variability is significantly linked to AOD, WS, NOx, Preci and CLF. Also zone-5, consisting of tropical monsoon areas of eastern India and Myanmar, is the only study zone over which all the selected parameters show their influence on tropo-NO2 at statistical significance levels. In stepwise multiple linear modeling, tropo-NO2 column over landmass of South Asia, is significantly predicted by the combination of RH (standardized regression coefficient, β = - 49), AOD (β = 0.42) and NOx (β = 0.25). The leading predictors of tropo-NO2 columns over zones 1-5 are OLR, AOD, Temp, OLR, and RH respectively. Overall, as revealed by the higher correlation coefficients (r), the multiple regressions provide reasonable models for tropo-NO2 over South Asia (r = 0.82), zone-4 (r = 0.90) and zone-5 (r = 0.93). The lowest r (of 0.66) has been found for hot semi-arid region in northwestern Indus-Ganges Basin (zone-2). The highest value of β for urban area AOD (of 0.42) is observed for megacity Lahore, located in warm semi-arid zone-2 with large scale crop-residue burning, indicating strong influence of aerosols on the modeled tropo-NO2 column. A statistical significant correlation (r = 0.22) at the 0.05 level is found between tropo-NO2 and AOD over Lahore. Also NOx emissions appear as the highest contributor (β = 0.59) for modeled tropo-NO2 column over megacity Dhaka.

  3. Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

    Science.gov (United States)

    Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

    2017-12-01

    An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

  4. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    Science.gov (United States)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

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

    Directory of Open Access Journals (Sweden)

    Matthew Geary

    Full Text Available 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.

  6. Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon

    KAUST Repository

    Attada, Raju

    2018-04-17

    Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena

  7. Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon

    Science.gov (United States)

    Attada, Raju; Kumar, Prashant; Dasari, Hari Prasad

    2018-04-01

    Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF-LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena in

  8. Assessment of Land Surface Models in a High-Resolution Atmospheric Model during Indian Summer Monsoon

    KAUST Repository

    Attada, Raju; Kumar, Prashant; Dasari, Hari Prasad

    2018-01-01

    Assessment of the land surface models (LSMs) on monsoon studies over the Indian summer monsoon (ISM) region is essential. In this study, we evaluate the skill of LSMs at 10 km spatial resolution in simulating the 2010 monsoon season. The thermal diffusion scheme (TDS), rapid update cycle (RUC), and Noah and Noah with multi-parameterization (Noah-MP) LSMs are chosen based on nature of complexity, that is, from simple slab model to multi-parameterization options coupled with the Weather Research and Forecasting (WRF) model. Model results are compared with the available in situ observations and reanalysis fields. The sensitivity of monsoon elements, surface characteristics, and vertical structures to different LSMs is discussed. Our results reveal that the monsoon features are reproduced by WRF model with all LSMs, but with some regional discrepancies. The model simulations with selected LSMs are able to reproduce the broad rainfall patterns, orography-induced rainfall over the Himalayan region, and dry zone over the southern tip of India. The unrealistic precipitation pattern over the equatorial western Indian Ocean is simulated by WRF–LSM-based experiments. The spatial and temporal distributions of top 2-m soil characteristics (soil temperature and soil moisture) are well represented in RUC and Noah-MP LSM-based experiments during the ISM. Results show that the WRF simulations with RUC, Noah, and Noah-MP LSM-based experiments significantly improved the skill of 2-m temperature and moisture compared to TDS (chosen as a base) LSM-based experiments. Furthermore, the simulations with Noah, RUC, and Noah-MP LSMs exhibit minimum error in thermodynamics fields. In case of surface wind speed, TDS LSM performed better compared to other LSM experiments. A significant improvement is noticeable in simulating rainfall by WRF model with Noah, RUC, and Noah-MP LSMs over TDS LSM. Thus, this study emphasis the importance of choosing/improving LSMs for simulating the ISM phenomena

  9. PROCRU: A model for analyzing crew procedures in approach to landing

    Science.gov (United States)

    Baron, S.; Muralidharan, R.; Lancraft, R.; Zacharias, G.

    1980-01-01

    A model for analyzing crew procedures in approach to landing is developed. The model employs the information processing structure used in the optimal control model and in recent models for monitoring and failure detection. Mechanisms are added to this basic structure to model crew decision making in this multi task environment. Decisions are based on probability assessments and potential mission impact (or gain). Sub models for procedural activities are included. The model distinguishes among external visual, instrument visual, and auditory sources of information. The external visual scene perception models incorporate limitations in obtaining information. The auditory information channel contains a buffer to allow for storage in memory until that information can be processed.

  10. PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

    Directory of Open Access Journals (Sweden)

    Yaolin Liu

    Full Text Available Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

  11. Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016

    Directory of Open Access Journals (Sweden)

    Fidele Karamage

    2017-02-01

    Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.

  12. Monitoring and Modeling of Spatiotemporal Urban Expansion and Land-Use/Land-Cover Change Using Integrated Markov Chain Cellular Automata Model

    Directory of Open Access Journals (Sweden)

    Bhagawat Rimal

    2017-09-01

    Full Text Available Spatial–temporal analysis of land-use/land-cover (LULC change as well as the monitoring and modeling of urban expansion are essential for the planning and management of urban environments. Such environments reflect the economic conditions and quality of life of the individual country. Urbanization is generally influenced by national laws, plans and policies and by power, politics and poor governance in many less-developed countries. Remote sensing tools play a vital role in monitoring LULC change and measuring the rate of urbanization at both the local and global levels. The current study evaluated the LULC changes and urban expansion of Jhapa district of Nepal. The spatial–temporal dynamics of LULC were identified using six time-series atmospherically-corrected surface reflectance Landsat images from 1989 to 2016. A hybrid cellular automata Markov chain (CA–Markov model was used to simulate future urbanization by 2026 and 2036. The analysis shows that the urban area has increased markedly and is expected to continue to grow rapidly in the future, whereas the area for agriculture has decreased. Meanwhile, forest and shrub areas have remained almost constant. Seasonal rainfall and flooding routinely cause predictable transformation of sand, water bodies and cultivated land from one type to another. The results suggest that the use of Landsat time-series archive images and the CA–Markov model are the best options for long-term spatiotemporal analysis and achieving an acceptable level of prediction accuracy. Furthermore, understanding the relationship between the spatiotemporal dynamics of urbanization and LULC change and simulating future landscape change is essential, as they are closely interlinked. These scientific findings of past, present and future land-cover scenarios of the study area will assist planners/decision-makers to formulate sustainable urban development and environmental protection plans and will remain a scientific asset

  13. Spatial stochastic regression modelling of urban land use

    International Nuclear Information System (INIS)

    Arshad, S H M; Jaafar, J; Abiden, M Z Z; Latif, Z A; Rasam, A R A

    2014-01-01

    Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable

  14. Site selection model for new metro stations based on land use

    Science.gov (United States)

    Zhang, Nan; Chen, Xuewu

    2015-12-01

    Since the construction of metro system generally lags behind the development of urban land use, sites of metro stations should adapt to their surrounding situations, which was rarely discussed by previous research on station layout. This paper proposes a new site selection model to find the best location for a metro station, establishing the indicator system based on land use and combining AHP with entropy weight method to obtain the schemes' ranking. The feasibility and efficiency of this model has been validated by evaluating Nanjing Shengtai Road station and other potential sites.

  15. Fuzzy Optimization of Option Pricing Model and Its Application in Land Expropriation

    Directory of Open Access Journals (Sweden)

    Aimin Heng

    2014-01-01

    Full Text Available Option pricing is irreversible, fuzzy, and flexible. The fuzzy measure which is used for real option pricing is a useful supplement to the traditional real option pricing method. Based on the review of the concepts of the mean and variance of trapezoidal fuzzy number and the combination with the Carlsson-Fuller model, the trapezoidal fuzzy variable can be used to represent the current price of land expropriation and the sale price of land on the option day. Fuzzy Black-Scholes option pricing model can be constructed under fuzzy environment and problems also can be solved and discussed through numerical examples.

  16. WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

    Science.gov (United States)

    Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

    2014-05-01

    Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are

  17. Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

    Science.gov (United States)

    Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

    2017-12-01

    Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides

  18. Parameterization Improvements and Functional and Structural Advances in Version 4 of the Community Land Model

    Directory of Open Access Journals (Sweden)

    Andrew G. Slater

    2011-05-01

    Full Text Available The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon-nitrogen (CN biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating –– as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ~50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, atmospheric forcing height, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated.Taken together, these augmentations to CLM result in improved soil moisture dynamics, drier soils, and stronger soil moisture variability. The new model also exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is slightly degraded because the vegetation structure is prognostic rather

  19. Divergent projections of future land use in the United States arising from different models and scenarios

    Science.gov (United States)

    Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.

    2016-01-01

    A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there

  20. Peak Vertical Ground Reaction Force during Two-Leg Landing: A Systematic Review and Mathematical Modeling

    Directory of Open Access Journals (Sweden)

    Wenxin Niu

    2014-01-01

    Full Text Available Objectives. (1 To systematically review peak vertical ground reaction force (PvGRF during two-leg drop landing from specific drop height (DH, (2 to construct a mathematical model describing correlations between PvGRF and DH, and (3 to analyze the effects of some factors on the pooled PvGRF regardless of DH. Methods. A computerized bibliographical search was conducted to extract PvGRF data on a single foot when participants landed with both feet from various DHs. An innovative mathematical model was constructed to analyze effects of gender, landing type, shoes, ankle stabilizers, surface stiffness and sample frequency on PvGRF based on the pooled data. Results. Pooled PvGRF and DH data of 26 articles showed that the square root function fits their relationship well. An experimental validation was also done on the regression equation for the medicum frequency. The PvGRF was not significantly affected by surface stiffness, but was significantly higher in men than women, the platform than suspended landing, the barefoot than shod condition, and ankle stabilizer than control condition, and higher than lower frequencies. Conclusions. The PvGRF and root DH showed a linear relationship. The mathematical modeling method with systematic review is helpful to analyze the influence factors during landing movement without considering DH.

  1. Dealing with uncertainties in impact studies of climate change on hydrometeorological series over Segura River Basin (Spain)

    Science.gov (United States)

    Garcia Galiano, S. G.; Garcia Cardenas, R.; Tetay Botia, C.; Giraldo Osorio, J.; Erena Arrabal, M.; Baille, A.

    2011-12-01

    The Segura River Basin (SRB) located in the South East of Spain, is affected by recurrent drought and water scarcity episodes. This basin presents the lowest percentage of renewable water resources of all the Spanish basins. Intensive reforestation has been carried out in the region, to halt desertification and erosion, which added to climate change and variability, do not allow the default assumption of stationarity in the water resources systems. Therefore, the study of effects in hydrometeorological series should be addressed by nonstationary probabilistic models that allow describing the time evolution of their probability distribution functions (PDFs). In the present work, the GAMLSS (Generalized Additive Models for Location, Scale and Shaper) approach is applied to identify of spatio-temporal trends in observed precipitation (P) and potential evapotranspiration (PET), at basin scale. Several previous studies have addressed the potential impacts of climate change in water supply systems, focusing on the sensitivity analysis of runoff to climate. Considering the use of a conceptual hydrological model with few parameters, the impacts on runoff and its trend from historical data, are assessed. The conclusions of this study represent a breakthrough in the development of methodologies to understand and anticipate the impacts on water resources systems, in the light of current and future climate conditions, considering hydroclimatic non-stationarity. These findings are expected to contribute to the management of conditions of water resources scarcity and droughts, such as the observed in the SRB, as support to decision-making process by stakeholders.

  2. Assessing the influence of groundwater and land surface scheme in the modelling of land surface-atmosphere feedbacks over the FIFE area in Kansas, USA

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Højmark Rasmussen, Søren; Drews, Martin

    2016-01-01

    The land surface-atmosphere interaction is described differently in large scale surface schemes of regional climate models and small scale spatially distributed hydrological models. In particular, the hydrological models include the influence of shallow groundwater on evapotranspiration during dry...... by HIRHAM simulated precipitation. The last two simulations include iv) a standard HIRHAM simulation, and v) a fully coupled HIRHAM-MIKE SHE simulation locally replacing the land surface scheme by MIKE SHE for the FIFE area, while HIRHAM in standard configuration is used for the remaining model area...

  3. Integrated Multimedia Modeling System Response to Regional Land Management Change

    Science.gov (United States)

    A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of research and development. It is ...

  4. Export of microplastics from land to sea. A modelling approach

    NARCIS (Netherlands)

    Siegfried, Max; Koelmans, A.A.; Besseling, E.; Kroeze, C.

    2017-01-01

    Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea.

  5. Multidimensional Numerical Modeling of Surges Over Initially Dry Land

    National Research Council Canada - National Science Library

    Berger, R

    2004-01-01

    .... The first test case is for a straight flume and the second contains a reservoir and a horseshoe channel section. It is important that the model match the timing of the surge as well as the height In both cases the ADH compared closely with the flume results.

  6. Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0

    Directory of Open Access Journals (Sweden)

    G. Bisht

    2017-12-01

    Full Text Available A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5 and a massively parallel multiphysics reactive transport model (PFLOTRAN. The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result

  7. Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream-aquifer-land interactions (CP v1.0)

    Science.gov (United States)

    Bisht, Gautam; Huang, Maoyi; Zhou, Tian; Chen, Xingyuan; Dai, Heng; Hammond, Glenn E.; Riley, William J.; Downs, Janelle L.; Liu, Ying; Zachara, John M.

    2017-12-01

    A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater-river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater-river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater-river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the

  8. Export of microplastics from land to sea. A modelling approach.

    Science.gov (United States)

    Siegfried, Max; Koelmans, Albert A; Besseling, Ellen; Kroeze, Carolien

    2017-12-15

    Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea. The model accounts for different types and sources of microplastics entering river systems via point sources. We combine information on these sources with information on sewage management and plastic retention during river transport for the largest European rivers. Sources of microplastics include personal care products, laundry, household dust and tyre and road wear particles (TRWP). Most of the modelled microplastics exported by rivers to seas are synthetic polymers from TRWP (42%) and plastic-based textiles abraded during laundry (29%). Smaller sources are synthetic polymers and plastic fibres in household dust (19%) and microbeads in personal care products (10%). Microplastic export differs largely among European rivers, as a result of differences in socio-economic development and technological status of sewage treatment facilities. About two-thirds of the microplastics modelled in this study flow into the Mediterranean and Black Sea. This can be explained by the relatively low microplastic removal efficiency of sewage treatment plants in the river basins draining into these two seas. Sewage treatment is generally more efficient in river basins draining into the North Sea, the Baltic Sea and the Atlantic Ocean. We use our model to explore future trends up to the year 2050. Our scenarios indicate that in the future river export of microplastics may increase in some river basins, but decrease in others. Remarkably, for many basins we calculate a reduction in river export of microplastics from point-sources, mainly due to an anticipated improvement in sewage treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Application of the WEPS and SWEEP models to non-agricultural disturbed lands

    Directory of Open Access Journals (Sweden)

    J. Tatarko

    2016-12-01

    Full Text Available Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10 has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP, has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but

  10. Application of the WEPS and SWEEP models to non-agricultural disturbed lands.

    Science.gov (United States)

    Tatarko, J; van Donk, S J; Ascough, J C; Walker, D G

    2016-12-01

    Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10) has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS) was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP), has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily) wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year) erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but also incorporate

  11. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Directory of Open Access Journals (Sweden)

    S. Naha

    2016-06-01

    Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

  12. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    Directory of Open Access Journals (Sweden)

    H. W. Ter Maat

    2010-08-01

    Full Text Available This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS, coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C, and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables.

    The simulations performed with the coupled regional model (RAMS-SWAPS-C are in good qualitative agreement with the observations. The station validation of the model demonstrates that the incoming shortwave radiation and surface fluxes of water and CO2 are well simulated. The comparison against aircraft data shows that the regional meteorology (i.e. wind, temperature is captured well by the model. Comparing spatially explicitly simulated fluxes with aircraft observed fluxes we conclude that in general latent heat fluxes are underestimated by the model compared to the observations but that the latter exhibit large variability within all flights. Sensitivity experiments demonstrate the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same tests also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

  13. Modelling land-use effects of future urbanization using cellular automata

    DEFF Research Database (Denmark)

    Fuglsang, Morten; Münier, B.; Hansen, H.S.

    2013-01-01

    project PASHMINA (Paradigm Shift modelling and innovative approaches), three storylines of future transportation paradigm shifts towards 2040 are created. These storylines are translated into spatial planning strategies and modelled using the cellular automata model LUCIA. For the modelling, an Eastern......The modelling of land use change is a way to analyse future scenarios by modelling different pathways. Application of spatial data of different scales coupled with socio-economic data makes it possible to explore and test the understanding of land use change relations. In the EU-FP7 research...... Danish case area was selected, comprising of the Copenhagen metropolitan area and its hinterland. The different scenarios are described using a range of different descriptive GIS datasets. These include mapping of accessibility based on public and private transportation, urban density and structure...

  14. Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China

    Directory of Open Access Journals (Sweden)

    Yuanyuan Yang

    2015-05-01

    Full Text Available Decadal to centennial land use and land cover change has been consistently singled out as a key element and an important driver of global environmental change, playing an essential role in balancing energy use. Understanding long-term human-environment interactions requires historical reconstruction of past land use and land cover changes. Most of the existing historical reconstructions have insufficient spatial and thematic detail and do not consider various land change types. In this context, this paper explored the possibility of using a cellular automata-Markov model in 90 m × 90 m spatial resolution to reconstruct historical land use in the 1930s in Zhenlai County, China. Then the three-map comparison methodology was employed to assess the predictive accuracy of the transition modeling. The model could produce backward projections by analyzing land use changes in recent decades, assuming that the present land use pattern is dynamically dependent on the historical one. The reconstruction results indicated that in the 1930s most of the study area was occupied by grasslands, followed by wetlands and arable land, while other land categories occupied relatively small areas. Analysis of the three-map comparison illustrated that the major differences among the three maps have less to do with the simulation model and more to do with the inconsistencies among the land categories during the study period. Different information provided by topographic maps and remote sensing images must be recognized.

  15. Clarity versus complexity: land-use modeling as a practical tool for decision-makers

    Science.gov (United States)

    Sohl, Terry L.; Claggett, Peter

    2013-01-01

    The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

  16. A model to predict impervious surface for regional and municipal land use planning purposes

    International Nuclear Information System (INIS)

    Reilly, James; Maggio, Patricia; Karp, Steven

    2004-01-01

    The area of impervious surface in a watershed is a forcing variable in many hydrologic models and has been proposed as a policy variable surrogate for water quality. We report a new statistical model which will allow land use planners to estimate impervious surface given minimal, readily available information about future growth. Our model is suitable for master planning purposes. In more urbanized areas, it tends to produce quite accurate forecasts. However, in less developed, more rural places, forecast error will increase

  17. Improving the Fit of a Land-Surface Model to Data Using its Adjoint

    Science.gov (United States)

    Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

    2015-12-01

    Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

  18. An Analytic Approach to Modeling Land-Atmosphere Interaction: 1. Construct and Equilibrium Behavior

    Science.gov (United States)

    Brubaker, Kaye L.; Entekhabi, Dara

    1995-03-01

    A four-variable land-atmosphere model is developed to investigate the coupled exchanges of water and energy between the land surface and atmosphere and the role of these exchanges in the statistical behavior of continental climates. The land-atmosphere system is substantially simplified and formulated as a set of ordinary differential equations that, with the addition of random noise, are suitable for analysis in the form of the multivariate Îto equation. The model treats the soil layer and the near-surface atmosphere as reservoirs with storage capacities for heat and water. The transfers between these reservoirs are regulated by four states: soil saturation, soil temperature, air specific humidity, and air potential temperature. The atmospheric reservoir is treated as a turbulently mixed boundary layer of fixed depth. Heat and moisture advection, precipitation, and layer-top air entrainment are parameterized. The system is forced externally by solar radiation and the lateral advection of air and water mass. The remaining energy and water mass exchanges are expressed in terms of the state variables. The model development and equilibrium solutions are presented. Although comparisons between observed data and steady state model results re inexact, the model appears to do a reasonable job of partitioning net radiation into sensible and latent heat flux in appropriate proportions for bare-soil midlatitude summer conditions. Subsequent work will introduce randomness into the forcing terms to investigate the effect of water-energy coupling and land-atmosphere interaction on variability and persistence in the climatic system.

  19. Land-use regression panel models of NO2 concentrations in Seoul, Korea

    Science.gov (United States)

    Kim, Youngkook; Guldmann, Jean-Michel

    2015-04-01

    Transportation and land-use activities are major air pollution contributors. Since their shares of emissions vary across space and time, so do air pollution concentrations. Despite these variations, panel data have rarely been used in land-use regression (LUR) modeling of air pollution. In addition, the complex interactions between traffic flows, land uses, and meteorological variables, have not been satisfactorily investigated in LUR models. The purpose of this research is to develop and estimate nitrogen dioxide (NO2) panel models based on the LUR framework with data for Seoul, Korea, accounting for the impacts of these variables, and their interactions with spatial and temporal dummy variables. The panel data vary over several scales: daily (24 h), seasonally (4), and spatially (34 intra-urban measurement locations). To enhance model explanatory power, wind direction and distance decay effects are accounted for. The results show that vehicle-kilometers-traveled (VKT) and solar radiation have statistically strong positive and negative impacts on NO2 concentrations across the four seasonal models. In addition, there are significant interactions with the dummy variables, pointing to VKT and solar radiation effects on NO2 concentrations that vary with time and intra-urban location. The results also show that residential, commercial, and industrial land uses, and wind speed, temperature, and humidity, all impact NO2 concentrations. The R2 vary between 0.95 and 0.98.

  20. LAND SUITABILITY SCENARIOS FOR ARID COASTAL PLAINS USING GIS MODELING: SOUTHWESTERN SINAI COASTAL PLAIN, EGYPT

    Directory of Open Access Journals (Sweden)

    Ahmed Mohamed Wahid

    2009-12-01

    Full Text Available Site selection analysis was carried out to find the best suitable lands for development activities in an example of promising coastal plains, southwestern Sinai, Egypt. Two GIS models were developed to represent two scenarios of land use suitability in the study area using GIS Multi Criteria Analysis Modeling. The factors contributed in the analysis are the Topography, Land cover, Existing Land use, Flash flood index, Drainage lines and Water points. The first scenario was to classify the area according to various gradual ranges of suitability. According to this scenario, the area is classified into five classes of suitability. The percentage of suitability values are 51.16, 6.13, 22.32, 18.49 and 1.89% for unsuitable, least suitable, low suitable, suitable and high suitable, respectively. The second scenario is developed for a particular kind of land use planning; tourism and recreation projects. The suitability map of this scenario was classified into five values. Unsuitable areas represent 51.18% of the study area, least suitable 16.67%, low suitable 22.85%, suitable 8.61%, and high suitable 0.68%. The best area for locating development projects is the area surrounding El-Tor City and close to the coast. This area could be an urban extension of El-Tor City with more economical and environmental management.

  1. Impacts of land-use change on the water cycle of urban areas within the Upper Great Lakes drainage basin

    Science.gov (United States)

    Bowling, L. C.; Cherkauer, K. A.; Pijanowski, B. C.; Niyogi, D.

    2006-12-01

    Urbanization is altering the global landscape at an unprecedented rate. This form of land cover/land-use change (LCLUC) can significantly reduce infiltration and runoff response times, and alter heat and water vapor fluxes, which can further alter surface-forced regional circulation patterns and modulate precipitation volume and intensity. Spatial patterns of future LCLUC are projected using the Land Transformation Model (LTM), enhanced to incorporate dynamic landcover, economics and policy using Bayesian Belief Networks (LTM- BBN). Different land use scenarios predicted by the LTM-BBN as well as a pre-development scenario are represented through the Unified Noah Land Surface Model (LSM) with an enhanced urban canopy model, embedded in the Weather Research and Forecasting (WRF) model. The coupled WRF-Noah LSM model will be used to investigate the connections between land-use, hydrometeorology and the atmosphere, through analysis of water and energy balances over several urbanized watersheds within the Upper Great Lakes region. Preliminary results focus on a single watershed, the White River in Indiana, which includes the city of Indianapolis. Coupled WRF-Noah simulations made using pre and post-development land use maps provide a 7 year climatology of convective storm morphology around the urban center. Precipitation and other meteorological variables from the WRF-Noah simulations are used to drive simulations of the White River watershed using the Variable Infiltration Capacity (VIC) macroscale hydrologic model. The VIC model has been modified to represent urban areas and has been calibrated for modern flow regimes in the White River watershed. Pre- and post-development VIC simulations are used to assess the impact of Indianapolis area infiltration changes. Finally, VIC model simulations utilizing projected land use change from 2005 through 2040 for the Indianapolis metropolitan area explore the magnitude of future hydrologic change, especially peak flow response

  2. ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

    Science.gov (United States)

    Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

    2012-06-01

    It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil

  3. ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

    Directory of Open Access Journals (Sweden)

    T. Bedrina

    2012-06-01

    Full Text Available It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR. Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS networks, capable to provide almost real-time, location aware, weather data.

    Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps.

    This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in

  4. Using Intel's Knight Landing Processor to Accelerate Global Nested Air Quality Prediction Modeling System (GNAQPMS) Model

    Science.gov (United States)

    Wang, H.; Chen, H.; Chen, X.; Wu, Q.; Wang, Z.

    2016-12-01

    The Global Nested Air Quality Prediction Modeling System for Hg (GNAQPMS-Hg) is a global chemical transport model coupled Hg transport module to investigate the mercury pollution. In this study, we present our work of transplanting the GNAQPMS model on Intel Xeon Phi processor, Knights Landing (KNL) to accelerate the model. KNL is the second-generation product adopting Many Integrated Core Architecture (MIC) architecture. Compared with the first generation Knight Corner (KNC), KNL has more new hardware features, that it can be used as unique processor as well as coprocessor with other CPU. According to the Vtune tool, the high overhead modules in GNAQPMS model have been addressed, including CBMZ gas chemistry, advection and convection module, and wet deposition module. These high overhead modules were accelerated by optimizing code and using new techniques of KNL. The following optimized measures was done: 1) Changing the pure MPI parallel mode to hybrid parallel mode with MPI and OpenMP; 2.Vectorizing the code to using the 512-bit wide vector computation unit. 3. Reducing unnecessary memory access and calculation. 4. Reducing Thread Local Storage (TLS) for common variables with each OpenMP thread in CBMZ. 5. Changing the way of global communication from files writing and reading to MPI functions. After optimization, the performance of GNAQPMS is greatly increased both on CPU and KNL platform, the single-node test showed that optimized version has 2.6x speedup on two sockets CPU platform and 3.3x speedup on one socket KNL platform compared with the baseline version code, which means the KNL has 1.29x speedup when compared with 2 sockets CPU platform.

  5. Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

    Science.gov (United States)

    Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

    2013-12-01

    This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

  6. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002 (NLDAS_NOAH0125_H) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  7. An analysis of the evolution of hydrometeorological extremes in newspapers: the case of Catalonia, 1982–2006

    Directory of Open Access Journals (Sweden)

    V. Altava-Ortiz

    2009-07-01

    Full Text Available This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (INUNGAMA has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use.

  8. An analysis of the evolution of hydrometeorological extremes in newspapers: the case of Catalonia, 1982-2006

    Science.gov (United States)

    Llasat, M. C.; Llasat-Botija, M.; Barnolas, M.; López, L.; Altava-Ortiz, V.

    2009-07-01

    This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation) has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (INUNGAMA) has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use.

  9. Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

    Science.gov (United States)

    Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

    2012-01-01

    Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

  10. The quest for the perfect model: Pre World War 1. Military land use modeling of the Greater Copenhagen area

    DEFF Research Database (Denmark)

    Svenningsen, Stig Roar; Brandt, Jesper; Christensen, Andreas Aagaard

    the rotational system. At first the survey campaign seems to be going very well, but relative quickly did the military run into problems. The rapid urbanization of the landscape north of Copenhagen meant, that farming did not take place and at the island of Amager southwest of Copenhagen the farmers didn’t use......Anthropogenic land use practices are the single most important factor in the changing European landscapes. Respectively much attention has been devoted within Landscape Ecology to analyze changing patterns of land use and develop research strategies to understand the processes behind these changes...... and to inform policy makers. Models are used as an important tool in this research partly due to the revolution in information technologies during the last 30 years, which has made modeling more widespread in the research community. However modeling human decision making in form of land use practices...

  11. Land transportation model for supply chain manufacturing industries

    Science.gov (United States)

    Kurniawan, Fajar

    2017-12-01

    Supply chain is a system that integrates production, inventory, distribution and information processes for increasing productivity and minimize costs. Transportation is an important part of the supply chain system, especially for supporting the material distribution process, work in process products and final products. In fact, Jakarta as the distribution center of manufacturing industries for the industrial area. Transportation system has a large influences on the implementation of supply chain process efficiency. The main problem faced in Jakarta is traffic jam that will affect on the time of distribution. Based on the system dynamic model, there are several scenarios that can provide solutions to minimize timing of distribution that will effect on the cost such as the construction of ports approaching industrial areas other than Tanjung Priok, widening road facilities, development of railways system, and the development of distribution center.

  12. Long-range hydrometeorological ensemble predictions of drought parameters

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2012-06-01

    Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

  13. Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

    2012-12-01

    Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

  14. Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

    Science.gov (United States)

    Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

    2013-04-01

    Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

  15. Role of land state in a high resolution mesoscale model for ...

    Indian Academy of Sciences (India)

    13

    2015-10-02

    Oct 2, 2015 ... School of Earth, Ocean and Climate Sciences ... Though global models predicted the large scale event, but they had failed to predict realistic ... this study is to assess the impact of land state conditions in ...... Chand, R and C Singh 2015 Movements of western disturbance and associated cloud convection J.

  16. Procedural modeling of urban layout: population, land use, and road network

    NARCIS (Netherlands)

    Lyu, X.; Han, Q.; de Vries, B.

    2017-01-01

    This paper introduces an urban simulation system generating urban layouts with population, road network and land use layers. The desired urban spatial structure is obtained by generating a population map based on population density models. The road network is generated at two spatial levels

  17. Modelling soil organic carbon concentration of mineral soils in arable lands using legacy soil data

    DEFF Research Database (Denmark)

    Suuster, E; Ritz, Christian; Roostalu, H

    2012-01-01

    is appropriate if the study design has a hierarchical structure as in our scenario. We used the Estonian National Soil Monitoring data on arable lands to predict SOC concentrations of mineral soils. Subsequently, the model with the best prediction accuracy was applied to the Estonian digital soil map...

  18. Land use as a Driver of Patterns of Rodenticide Exposure in Modeled Kit Fox Populations

    Science.gov (United States)

    Although rodenticides are increasingly regulated, they nonetheless cause poisonings in many non-target wildlife species. Second-generation anticoagualant rodenticide use is common in agricultural and residential lands. Here, we use an individual-based population model to assess t...

  19. The road to a standard land administration domain model, and beyond ...

    NARCIS (Netherlands)

    Lemmen, C.H.J.; Uitermark, H.T.; Van Oosterom, P.J.M.; Zevenbergen, J.A.; Greenway, I.

    2011-01-01

    The Land Administration Domain Model (LADM) is a Draft International Standard (ISO DIS 19152) and in January 2011 was distributed by the ISO central secretariat for a five month voting and commenting time interval. If everything goes as planned, ISO 19152 will be an International Standard (IS) by

  20. An agent-based approach to model land-use change at a regional scale

    NARCIS (Netherlands)

    Valbuena, D.F.; Verburg, P.H.; Bregt, A.K.; Ligtenberg, A.

    2010-01-01

    Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local

  1. Firm dynamic analysis for urban land use and economic growth modelling

    NARCIS (Netherlands)

    Che'Man, N.; Sabri, S.; Hosni, N.; Timmermans, H.J.P.

    2013-01-01

    In urban growth processes, urbanisation is highly influenced by economic growth which triggers the dynamics of economic agents and land uses. This is consisted of complex subsystems which need sophisticated methods like agent-based modelling and simulation to understand the pattern, behaviour and

  2. Smaller global and regional carbon emissions from gross land use change when considering sub-grid secondary land cohorts in a global dynamic vegetation model

    Science.gov (United States)

    Yue, Chao; Ciais, Philippe; Li, Wei

    2018-02-01

    Several modelling studies reported elevated carbon emissions from historical land use change (ELUC) by including bidirectional transitions on the sub-grid scale (termed gross land use change), dominated by shifting cultivation and other land turnover processes. However, most dynamic global vegetation models (DGVMs) that have implemented gross land use change either do not account for sub-grid secondary lands, or often have only one single secondary land tile over a model grid cell and thus cannot account for various rotation lengths in shifting cultivation and associated secondary forest age dynamics. Therefore, it remains uncertain how realistic the past ELUC estimations are and how estimated ELUC will differ between the two modelling approaches with and without multiple sub-grid secondary land cohorts - in particular secondary forest cohorts. Here we investigated historical ELUC over 1501-2005 by including sub-grid forest age dynamics in a DGVM. We run two simulations, one with no secondary forests (Sageless) and the other with sub-grid secondary forests of six age classes whose demography is driven by historical land use change (Sage). Estimated global ELUC for 1501-2005 is 176 Pg C in Sage compared to 197 Pg C in Sageless. The lower ELUC values in Sage arise mainly from shifting cultivation in the tropics under an assumed constant rotation length of 15 years, being 27 Pg C in Sage in contrast to 46 Pg C in Sageless. Estimated cumulative ELUC values from wood harvest in the Sage simulation (31 Pg C) are however slightly higher than Sageless (27 Pg C) when the model is forced by reconstructed harvested areas because secondary forests targeted in Sage for harvest priority are insufficient to meet the prescribed harvest area, leading to wood harvest being dominated by old primary forests. An alternative approach to quantify wood harvest ELUC, i.e. always harvesting the close-to-mature forests in both Sageless and Sage, yields similar values of 33 Pg C by both

  3. What can and can't we say about indirect land-use change in Brazil using an integrated economic - land-use change model?

    NARCIS (Netherlands)

    Verstegen, J.A.; Hilst, van der Floor; Woltjer, Geert; Karssenberg, Derek; Jong, de S.M.; Faaij, André P.C.

    2016-01-01

    It is commonly recognized that large uncertainties exist in modelled biofuel-induced indirect land-use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general

  4. Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling

    Science.gov (United States)

    Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.

    2017-12-01

    For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce

  5. SENSING URBAN LAND-USE PATTERNS BY INTEGRATING GOOGLE TENSORFLOW AND SCENE-CLASSIFICATION MODELS

    Directory of Open Access Journals (Sweden)

    Y. Yao

    2017-09-01

    Full Text Available With the rapid progress of China’s urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model’s ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI. Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs. To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737 for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  6. From land use to land cover: Restoring the afforestation signal in a coupled integrated assessment - earth system model and the implications for CMIP5 RCP simulations

    Energy Technology Data Exchange (ETDEWEB)

    Di Vittorio, Alan V. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chini, Louise M. [Univ. of Maryland, College Park, MD (United States); Bond-Lamberty, Benjamin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mao, Jiafu [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shi, Xiaoying [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Truesdale, John E. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Craig, Anthony P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Calvin, Katherine V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Jones, Andrew D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Collins, William D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Edmonds, James A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hurtt, George [Univ. of Maryland, College Park, MD (United States); Thornton, Peter E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Thomson, Allison M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-11-27

    Climate projections depend on scenarios of fossil fuel emissions and land use change, and the IPCC AR5 parallel process assumes consistent climate scenarios across Integrated Assessment and Earth System Models (IAMs and ESMs). To facilitate consistency, CMIP5 used a novel land use harmonization to provide ESMs with seamless, 1500-2100 land use trajectories generated by historical data and four IAMs. However, we have identified and partially addressed a major gap in the CMIP5 land coupling design. The CMIP5 Community ESM (CESM) global afforestation is only 22% of RCP4.5 afforestation from 2005 to 2100. Likewise, only 17% of the Global Change Assessment Model’s (GCAM’s) 2040 RCP4.5 afforestation signal, and none of the pasture loss, were transmitted to CESM within a newly integrated model. This is a critical problem because afforestation is necessary for achieving the RCP4.5 climate stabilization. We attempted to rectify this problem by modifying only the ESM component of the integrated model, enabling CESM to simulate 66% of GCAM’s afforestation in 2040, and 94% of GCAM’s pasture loss as grassland and shrubland losses. This additional afforestation increases vegetation carbon gain by 19 PgC and decreases atmospheric CO2 gain by 8 ppmv from 2005 to 2040, implying different climate scenarios between CMIP5 GCAM and CESM. Similar inconsistencies likely exist in other CMIP5 model results, primarily because land cover information is not shared between models, with possible contributions from afforestation exceeding model-specific, potentially viable forest area. Further work to harmonize land cover among models will be required to adequately rectify this problem.

  7. Hydrometeorological aspects of the Real-Time Ultrafinescale Forecast Support during the Special Observing Period of the MAP*

    Directory of Open Access Journals (Sweden)

    R. Benoit

    2003-01-01

    Full Text Available During the Special Observation Period (SOP, 7 September–15 November, 1999 of the Mesoscale Alpine Programme (MAP, the Canadian Mesoscale Compressible Community Model (MC2 was run in real time at a horizontal resolution of 3 km on a computational domain of 350☓300☓50 grid points, covering the whole of the Alpine region. The WATFLOOD model was passively coupled to the MC2; the former is an integrated set of computer programs to forecast flood flows, using all available data, for catchments with response times ranging from one hour to several weeks. The unique aspect of this contribution is the operational application of numerical weather prediction data to forecast flows over a very large, multinational domain. An overview of the system performance from the hydrometeorological aspect is presented, mostly for the real-time results, but also from subsequent analyses. A streamflow validation of the precipitation is included for large basins covering upper parts of the Rhine and the Rhone, and parts of the Po and of the Danube. In general, the MC2/WATFLOOD model underestimated the total runoff because of the under-prediction of precipitation by MC2 during the MAP SOP. After the field experiment, a coding error in the cloud microphysics scheme of MC2 explains this underestimation to a large extent. A sensitivity study revealed that the simulated flows reproduce the major features of the observed flow record for most of the flow stations. The experiment was considered successful because two out of three possible flood events in the Swiss-Italian border region were predicted correctly by data from the numerical weather models linked to the hydrological model and no flow events were missed. This study has demonstrated that a flow forecast from a coupled atmospheric-hydrological model can serve as a useful first alert and quantitative forecast. Keywords: mesoscale atmospheric model, hydrological model, flood forecasting, Alps

  8. Calibration of a Land Subsidence Model Using InSAR Data via the Ensemble Kalman Filter.

    Science.gov (United States)

    Li, Liangping; Zhang, Meijing; Katzenstein, Kurt

    2017-11-01

    The application of interferometric synthetic aperture radar (InSAR) has been increasingly used to improve capabilities to model land subsidence in hydrogeologic studies. A number of investigations over the last decade show how spatially detailed time-lapse images of ground displacements could be utilized to advance our understanding for better predictions. In this work, we use simulated land subsidences as observed measurements, mimicking InSAR data to inversely infer inelastic specific storage in a stochastic framework. The inelastic specific storage is assumed as a random variable and modeled using a geostatistical method such that the detailed variations in space could be represented and also that the uncertainties of both characterization of specific storage and prediction of land subsidence can be assessed. The ensemble Kalman filter (EnKF), a real-time data assimilation algorithm, is used to inversely calibrate a land subsidence model by matching simulated subsidences with InSAR data. The performance of the EnKF is demonstrated in a synthetic example in which simulated surface deformations using a reference field are assumed as InSAR data for inverse modeling. The results indicate: (1) the EnKF can be used successfully to calibrate a land subsidence model with InSAR data; the estimation of inelastic specific storage is improved, and uncertainty of prediction is reduced, when all the data are accounted for; and (2) if the same ensemble is used to estimate Kalman gain, the analysis errors could cause filter divergence; thus, it is essential to include localization in the EnKF for InSAR data assimilation. © 2017, National Ground Water Association.

  9. A critical assessment of the JULES land surface model hydrology for humid tropical environments

    Science.gov (United States)

    Zulkafli, Z.; Buytaert, W.; Onof, C.; Lavado, W.; Guyot, J. L.

    2013-03-01

    Global land surface models (LSMs) such as the Joint UK Land Environment Simulator (JULES) are originally developed to provide surface boundary conditions for climate models. They are increasingly used for hydrological simulation, for instance to simulate the impacts of land use changes and other perturbations on the water cycle. This study investigates how well such models represent the major hydrological fluxes at the relevant spatial and temporal scales - an important question for reliable model applications in poorly understood, data-scarce environments. The JULES-LSM is implemented in a 360 000 km2 humid tropical mountain basin of the Peruvian Andes-Amazon at 12-km grid resolution, forced with daily satellite and climate reanalysis data. The simulations are evaluated using conventional discharge-based evaluation methods, and by further comparing the magnitude and internal variability of the basin surface fluxes such as evapotranspiration, throughfall, and surface and subsurface runoff of the model with those observed in similar environments elsewhere. We find reasonably positive model efficiencies and high correlations between the simulated and observed streamflows, but high root-mean-square errors affecting the performance in smaller, upper sub-basins. We attribute this to errors in the water balance and JULES-LSM's inability to model baseflow. We also found a tendency to under-represent the high evapotranspiration rates of the region. We conclude that strategies to improve the representation of tropical systems to be (1) addressing errors in the forcing and (2) incorporating local wetland and regional floodplain in the subsurface representation.

  10. An open and extensible framework for spatially explicit land use change modelling: the lulcc R package

    Science.gov (United States)

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

    2015-10-01

    We present the lulcc software 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 alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment.

  11. Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

    Directory of Open Access Journals (Sweden)

    Risto K Heikkinen

    Full Text Available Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina and one generalist (Issoria lathonia. Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity, with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

  12. Overview of Hydrometeorologic Forecasting Procedures at BC Hydro

    Science.gov (United States)

    McCollor, D.

    2004-12-01

    Energy utility companies must balance production from limited sources with increasing demand from industrial, business, and residential consumers. The utility planning process requires a balanced, efficient, and effective distribution of energy from source to consumer. Therefore utility planners must consider the impact of weather on energy production and consumption. Hydro-electric companies should be particularly tuned to weather because their source of energy is water, and water supply depends on precipitation. BC Hydro operates as the largest hydro-electric company in western Canada, managing over 30 reservoirs within the province of British Columbia, and generating electricity for 1.6 million people. BC Hydro relies on weather forecasts of watershed precipitation and temperature to drive hydrologic reservoir inflow models and of urban temperatures to meet energy demand requirements. Operations and planning specialists in the company rely on current, value-added weather forecasts for extreme high-inflow events, daily reservoir operations planning, and long-term water resource management. Weather plays a dominant role for BC Hydro financial planners in terms of sensitive economic responses. For example, a two percent change in hydropower generation, due in large part to annual precipitation patterns, results in an annual net change of \\50 million in earnings. A five percent change in temperature produces a \\5 million change in yearly earnings. On a daily basis, significant precipitation events or temperature extremes involve potential profit/loss decisions in the tens of thousands of dollars worth of power generation. These factors are in addition to environmental and societal costs that must be considered equally as part of a triple bottom line reporting structure. BC Hydro water resource managers require improved meteorological information from recent advancements in numerical weather prediction. At BC Hydro, methods of providing meteorological forecast data

  13. Stochastic modeling of a hazard detection and avoidance maneuver—The planetary landing case

    International Nuclear Information System (INIS)

    Witte, Lars

    2013-01-01

    Hazard Detection and Avoidance (HDA) functionalities, thus the ability to recognize and avoid potential hazardous terrain features, is regarded as an enabling technology for upcoming robotic planetary landing missions. In the forefront of any landing mission the landing site safety assessment is an important task in the systems and mission engineering process. To contribute to this task, this paper presents a mathematical framework to consider the HDA strategy and system constraints in this mission engineering aspect. Therefore the HDA maneuver is modeled as a stochastic decision process based on Markov chains to map an initial dispersion at an arrival gate to a new dispersion pattern affected by the divert decision-making and system constraints. The implications for an efficient numerical implementation are addressed. An example case study is given to demonstrate the implementation and use of the proposed scheme

  14. Land suitability assessment in the catchment area of four Southwestern Atlantic coastal lagoons: multicriteria and optimization modeling.

    Science.gov (United States)

    Rodriguez-Gallego, Lorena; Achkar, Marcel; Conde, Daniel

    2012-07-01

    In the present study, a land suitability assessment was conducted in the basin of four Uruguayan coastal lagoons (Southwestern Atlantic) to analyze the productive development while minimizing eutrophication, biodiversity loss and conflicts among different land uses. Suitable land for agriculture, forest, livestock ranching, tourism and conservation sectors were initially established based on a multi-attribute model developed using a geographic information system. Experts were consulted to determine the requirements for each land use sector and the incompatibilities among land use types. The current and potential conflicts among incompatible land use sectors were analyzed by overlapping land suitability maps. We subsequently applied a multi-objective model where land (pixels) with similar suitability was clustered into "land suitability groups", using a two-phase cluster analysis and the Akaike Information Criterion. Finally, a linear programming optimization procedure was applied to allocate land use sectors into land suitable groups, maximizing total suitability and minimizing interference among sectors. Results indicated that current land use overlapped by 4.7 % with suitable land of other incompatible sectors. However, the suitable land of incompatible sectors overlapped in 20.3 % of the study area, indicating a high potential for the occurrence of future conflict. The highest competition was between agriculture and conservation, followed by forest and agriculture. We explored scenarios where livestock ranching and tourism intensified, and found that interference with conservation and agriculture notably increased. This methodology allowed us to analyze current and potential land use conflicts and to contribute to the strategic planning of the study area.

  15. Modeling Occurrence of Urban Mosquitos Based on Land Use Types and Meteorological Factors in Korea

    Directory of Open Access Journals (Sweden)

    Yong-Su Kwon

    2015-10-01

    Full Text Available Mosquitoes are a public health concern because they are vectors of pathogen, which cause human-related diseases. It is well known that the occurrence of mosquitoes is highly influenced by meteorological conditions (e.g., temperature and precipitation and land use, but there are insufficient studies quantifying their impacts. Therefore, three analytical methods were applied to determine the relationships between urban mosquito occurrence, land use type, and meteorological factors: cluster analysis based on land use types; principal component analysis (PCA based on mosquito occurrence; and three prediction models, support vector machine (SVM, classification and regression tree (CART, and random forest (RF. We used mosquito data collected at 12 sites from 2011 to 2012. Mosquito abundance was highest from August to September in both years. The monitoring sites were differentiated into three clusters based on differences in land use type such as culture and sport areas, inland water, artificial grasslands, and traffic areas. These clusters were well reflected in PCA ordinations, indicating that mosquito occurrence was highly influenced by land use types. Lastly, the RF represented the highest predictive power for mosquito occurrence and temperature-related factors were the most influential. Our study will contribute to effective control and management of mosquito occurrences.

  16. Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting.

    Science.gov (United States)

    Jahanishakib, Fatemeh; Mirkarimi, Seyed Hamed; Salmanmahiny, Abdolrassoul; Poodat, Fatemeh

    2018-05-08

    Efficient land use management requires awareness of past changes, present actions, and plans for future developments. Part of these requirements is achieved using scenarios that describe a future situation and the course of changes. This research aims to link scenario results with spatially explicit and quantitative forecasting of land use development. To develop land use scenarios, SMIC PROB-EXPERT and MORPHOL methods were used. It revealed eight scenarios as the most probable. To apply the scenarios, we considered population growth rate and used a cellular automata-Markov chain (CA-MC) model to implement the quantified changes described by each scenario. For each scenario, a set of landscape metrics was used to assess the ecological integrity of land use classes in terms of fragmentation and structural connectivity. The approach enabled us to develop spatial scenarios of land use change and detect their differences for choosing the most integrated landscape pattern in terms of landscape metrics. Finally, the comparison between paired forecasted scenarios based on landscape metrics indicates that scenarios 1-1, 2-2, 3-2, and 4-1 have a more suitable integrity. The proposed methodology for developing spatial scenarios helps executive managers to create scenarios with many repetitions and customize spatial patterns in real world applications and policies.

  17. Endangered Butterflies as a Model System for Managing Source Sink Dynamics on Department of Defense Lands

    Science.gov (United States)

    used three species of endangered butterflies as a model system to rigorously investigate the source-sink dynamics of species being managed on military...lands. Butterflies have numerous advantages as models for source-sink dynamics , including rapid generation times and relatively limited dispersal, but...they are subject to the same processes that determine source-sink dynamics of longer-lived, more vagile taxa.1.2 Technical Approach: For two of our

  18. Sensitivity of tsunami evacuation modeling to direction and land cover assumptions

    Science.gov (United States)

    Schmidtlein, Mathew C.; Wood, Nathan J.

    2015-01-01

    Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where