2,132 research outputs found

    Persepsi pengusaha warung makan terhadap pemasangan foto KH. Muhammad Zaini Abdul Ghani di Kecamatan Jekan Raya Kota Palangka Raya

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    Pemasangan foto KH. Muhammad Zaini Abdul Ghani oleh para pengusaha warung makan pada warung makannya merupakan fenomena yang sangat menarik. Pemasangan foto ulama tersebut tidak hanya terjadi pada satu atau dua warung makan, melainkan menjadi fenomena para pengusaha warung makan se-kota Palangka Raya. Penelitian ini bertujuan untuk menjawab masalah mengapa dan apa persepsi pengusaha warung makan mengenai pemasangan foto KH. Muhammad Zaini Abdul Ghani pada warung makan di Kecamatan Jekan Raya Kota Palangka Raya. Metode penelitian ini adalah kualitatif, dengan bentuk penelitian lapangan (field research). Teknik pengumpulan data menggunakan observasi, wawancara dan dokumentasi. Purposive sampling digunakan sebagai teknik sampling. Dan teknik analisis data yang digunakan adalah model Miles and Huberman yang terdiri dari data reduction, data display, dan conclution drawing. Hasil penelitian ini adalah, pertama alasan para pengusaha warung makan memasang foto KH. Muhammad Zaini Abdul Ghani pada warung makan di Kecamatan Jekan Raya Kota Palangka Raya sebagai media komunikasi non-verbal yang menginformasikan bahwa pemilik warung makan muslim, makanan yang disajikan halal, juga memberikan rasa aman dan nyaman bagi pelanggan. Kedua, persepsi pengusaha warung makan dilihat dari aspek kognisi, mereka mengetahui secara baik bahwa KH. Muhammad Zaini Abdul Ghani merupakan sosok ulama yang karismatik, sosok guru yang dikagumi, dan dihormati, kemudian aspek afeksi pemasangan foto dianggap sangat penting, dan dari aspek tindakan merupakan bagian dari praktek keagamaan sebagai tanda penghormatan dan kecintaan terhadap KH. Muhammad Zaini Abdul Ghani. ABSTRACT The installation of KH Muhammad Zaini Abdul Ghani's photo by the food stalls entrepreneurs at his food stall is a very interesting phenomenon. Installation of photographs of the moslem scholar not only occurred in one or two food stalls, but became the phenomenon of the food stalls entrepreneurs in the city of Palangka Raya. This study aims to answer the problem of why and what perceptions of food stalls entrepreneurs about the installation of photos KH Muhammad Zaini Abdul Ghani at food stalls in the district of Jekan Raya Palangka Raya city. This research method is qualitative, with field research form. Data collection techniques use observation, interview and documentation. Purposive sampling is used as a sampling technique. And data analysis technique used is Miles and Huberman model which consists of data reduction, display data, and conclution drawing. The result of this research is the first reason why the food stall entrepreneurs put the photo of KH Muhammad Zaini Abdul Ghani at the food stall in the district of Jekan Raya Palangka Raya city as a non-verbal communication media informing that the owner of Muslim food stall, the food served kosher, also gives safe and convenient for customers. Second, the perception of food stalls entrepreneurs viewed from the aspect of cognition, they know very well that KH Muhammad Zaini Abdul Ghani is a figure of a charismatic moslem scholar, the figure of an admired religious teacher, and respected, then the affective aspect of photo installation is considered very important, and from the aspect of action is part of religious practice as a sign of respect and love of KH Muhammad Zaini Abdul Ghani

    ECOHYDROLOGY IN MEDITERRANEAN AREAS: A NUMERICAL MODEL TO DESCRIBE GROWING SEASONS OUT OF PHASE WITH PRECIPITATIONS

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    The probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it. The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season. The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions. Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture. The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation

    Daily rainfall statistics in Sicily (1920-2000)

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    Rainfall characteristics are crucial for vegetation patterns formation and evolution in Mediterranean ecosystems. Changes in rainfall frequency and intensity could cause vegetation water stress for some plant species and benefit, at the same time, other species, driving coexistence and competition dynamics. The changes in the precipitation characteristics are sometimes more important than the changes in the total amount of precipitation in determining the partitioning between green and blue water with several implications for both the vegetation communities health and water resource management. Decreasing rainfall is a clear signature of climate change in Mediterranean countries. Annual and winter totals have been demonstrated to decrease in the past century and GCMs forecast a progressive worsening of the current situation even if it is still not clear if and how rainfall could be modified in its temporal and seasonal patterns. This study aims to analyze daily rainfall properties in Sicily in the last century. Namely the daily depths and interarrival times between events are investigated in about 50 stations, also characterizing seasonal rainfall features. The presence of significant trend has been detected using the non parametric Mann Kendall test

    Generation of natural runoff monthly series at ungauged sites using a regional regressive model

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    Many hydrologic applications require reliable estimates of runoff in river basins to face the widespread lack of data, both in time and in space. A regional method for the reconstruction of monthly runoff series is here developed and applied to Sicily (Italy). A simple modeling structure is adopted, consisting of a regression-based rainfall-runoff model with four model parameters, calibrated through a two-step procedure. Monthly runoff estimates are based on precipitation, temperature, and exploiting the autocorrelation with runoff at the previous month. Model parameters are assessed by specific regional equations as a function of easily measurable physical and climate basin descriptors. The first calibration step is aimed at the identification of a set of parameters optimizing model performances at the level of single basin. Such "optimal" sets are used at the second step, part of a regional regression analysis, to establish the regional equations for model parameters assessment as a function of basin attributes. All the gauged watersheds across the region have been analyzed, selecting 53 basins for model calibration and using the other six basins exclusively for validation. Performances, quantitatively evaluated by different statistical indexes, demonstrate relevant model ability in reproducing the observed hydrological time-series at both the monthly and coarser time resolutions. The methodology, which is easily transferable to other arid and semi-arid areas, provides a reliable tool for filling/reconstructing runoff time series at any gauged or ungauged basin of a region

    Climate changes effects on vegetation in Mediterranean areas

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    The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress

    Ecohydrology in Mediterranean areas: a numerical model to describe growing seasons out of phase with precipitations

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    International audienceThe probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it. The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season. The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions. Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture. The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation. The proposed model is applied to a case study characteristic of Mediterranean climate: the watershed of Eleuterio in Sicily (Italy)

    Modelling the shrub encroachment in a grassland with a Cellular Automata Model

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    Abstract. Arid and semi-arid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of shrub encroachment, i.e. the increase in density, cover and biomass of indigenous shrubby plants in grasslands. Numerous studies have documented the expansion of shrublands in the southwestern American grasslands; in particular shrub encroachment has occurred strongly in part of the northern Chihuahuan desert since 1860. This encroachment has been simulated using an ecohydrological Cellular Automata model, CATGraSS. It is a spatially distributed model driven by spatially explicit irradiance and runs on a fine-resolution gridded domain. Plant competition is modelled by keeping track of mortality and establishment of plants; both are calculated probabilistically based on soil moisture stress. For this study CATGraSS has been improved with a stochastic fire module and a grazing function. The model has been implemented in a small area in Sevilleta National Wildlife Refuge (SNWR), characterized by two vegetation types (grass savanna and creosote bush shrub), considering as encroachment causes the fire return period increase, the grazing increase, the seed dispersal caused by animals, the role of wind direction and plant type competition. The model is able to reproduce the encroachment that has occurred in SNWR, simulating an increase of the shrub from 2% in 1860 to the current shrub percentage, 42%, and highlighting among the most influential factors the reduced fire frequency and the increased grazing intensity

    Spatial analysis techniques for mapping the annual surface runoff in Sicily under the Budyko\u2019s framework

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    This work shows a new approach, based on the Budyko framework, for mapping the mean annual surface runoff and deriving the probability distribution of the annual runoff in arid and semi-arid watersheds. We analytically provide the annual runoff distribution as the derived distribution of annual rainfall and potential evapotranspiration. The simulated long-term annual runoff and its distribution have been compared with historical records at several gauged stations, obtaining satisfactory matching

    Numerical experiments for defining criteria for the use of LS-PIV based techniques in river monitoring.

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    The developing of new image-based techniques for environmental monitoring is opening new frontiers for remote streamflow measurements in natural environments, since they allow for non-intrusive measurements even in adverse circumstances, such as high flow conditions that often hinder the use of traditional approaches and instruments. Methods based on the acquisition, analysis and elaboration of images for streamflow observation, such as the large scale particle image velocimetry (LSPIV) and the particle tracking velocimetry (PTV) techniques, are rapidly evolving also in consideration of the growing availability of a new generation of optical sensors, digital cameras and methodologies. A number of free and easy software based on LSPIV and PTV allows for a complete characterization of the instantaneous surface velocity field of a river and the assessment of the discharge at specific cross-sections, when the cross-section geometry is known. This kind of software usually requires a sequence of images that can be captured by digital cameras, which can be permanent gauge-cams installed close to the river, mobile-devices with operators standing on the banks or on bridges, or even cams installed on unmanned aerial vehicle (UAV). Despite the great accessibility of cost-effective devices and the simplicity of the free availability of software for image processing, LSPIV and PTV techniques are rarely systematically implemented in practical applications, probably due to the lack of consistent image processing protocols. In this work the performance and the sensitivity of free software based on LSPIV to some factors, such as the seeding density, the frame to frame displacement of tracer, the number of elaborated frames, tracers geometry, are analyzed. In particular, difference sequences of images with known tracers (in size and density) moving at know velocity are created under different configurations (i.e. considering different combinations of the above mentioned factors) and the error in the evaluation of the instantaneous surface velocity field is assessed for each configuration. The different configurations are created considering three possible schemes: ideal (tracers constituted by white disks of equal size and uniformly distributed on a black background), semi-real (tracers constituted by disks of equal size, colored by a white color disturbed by a white noise, and uniformly distributed on a real background), real (real tracers on a real background). Real images, captured by a cam installed on UAV flying on a real river, have been used for the generation of the image-sequences generation under the schemes semi-real and real. Results can be considered extremely useful in defining criteria for guidelines for practical real applications

    Modeling the role of climate change on small-scale vegetation patterns in a Mediterranean basin using a Cellular Automata model

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    Predicting vegetation response in regions of ecotone transition under a changing climate is a among grand challenges in ecohydrology. In a small basin (1.3 sq km) in Sicily, Italy, where north-facing slopes are characterized by Quercus (tree), and south-facing slopes by Opuntia ficus-indaca (evergreen perennial species drought tolerant) and grasses we use an ecohydrological Cellular-Automaton model (CATGraSS) of vegetation coexistence driven by rainfall and solar radiation with downscaled future climate to examine the role of climate change on vegetation patterns. In the model, each cell can hold a single plant type or can be bare soil. Plant competition is modeled explicitly by keeping track of mortality and establishment of plants, both calculated probabilistically based on soil moisture stress. Topographic influence on incoming shortwave radiation is treated explicitly, which leads to spatial variations in potential evapotranspiration and resulting soil moisture and plant distribution. The influence of the soil thickness on the vegetation distribution is also introduced. The model is calibrated first using a representation of the current climate as a forcing and comparing the vegetation obtained from the model with the actual vegetation through statistical techniques.. The calibrated model is then forced with future climate scenarios generated using a stochastic downscaling technique based on the weather generator, AWE-GEN. This methodology allows for the downscaling of an ensemble of climate model outputs deriving the frequency distribution functions of factors of change for several statistics of temperature and precipitation from outputs of General Circulation Models. The stochastic downscaling is carried out using simulations of twelve General Circulation Models adopted in the IPCC 4AR, A1B emission scenario, for the future periods of 2046-2065 and 2081-2100. A high sensitivity of the vegetation distribution to variation of rainfall and temperature has been observed. The simulations suggest that the observed vegetation pattern can exist only in the current climate while the changes in the future storm characteristics could lead to a dramatic reorganization of the plant composition based mainly on the topography. Moreover the model analysis underscores the importance of solar irradiance in determining vegetation composition over complex terrain
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