Shahbaz Mehrabi; Mohammad Reza Yazdani; Mehdi Ghorbani
Abstract
Prevention is the most appropriate way to deal with natural hazards. And resilience means maintaining the structure and function of the socio-ecological system in the face of unexpected events, one of the important branches of prevention. Chaharmahal va Bakhtiari province, due to its specific geographical ...
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Prevention is the most appropriate way to deal with natural hazards. And resilience means maintaining the structure and function of the socio-ecological system in the face of unexpected events, one of the important branches of prevention. Chaharmahal va Bakhtiari province, due to its specific geographical location, faces numerous environmental hazards annually. Therefore, in this study, the status of resilience in the face of environmental hazards in the governing system of this province was investigated. AHP method was used for this purpose. In the AHP process, based on the pairwise comparison of criteria and sub-criteria, the degree of association between both criteria and sub-criteria is compared and scores between 1-9 are assigned. The research data was analyzed based on Delphi method and hierarchical decision making process. The results showed that according to expert’s evaluation of resilience of socio-ecological systems of Chaharmahal va Bakhtiari province against climate change (4.51), drought (2.09) and soil erosion (2.02) were ranked first to third respectively. Because of this, climate change has attracted the attention of experts who have shifted the rainfall to snow ratio over the past two decades. So that from 70% snow and 30% rain, to 70% rain and 30% snow. However, much of the economic activity and livelihoods in the province depend on snow reserves.
Fatemeh Maghsoud; Mohammad Reza Yazdani; Mohammad Rahimi; Arash Malekian; ali asghar zolfaghari
Abstract
Overview, drought is effected an unusual dry period which is enough continued and causes imbalance in the hydrologic status, as depletion of surface water and groundwater resources. The purpose of this research is modeling meteorological drought prediction using Neural Network- Multi layer Perceptron, ...
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Overview, drought is effected an unusual dry period which is enough continued and causes imbalance in the hydrologic status, as depletion of surface water and groundwater resources. The purpose of this research is modeling meteorological drought prediction using Neural Network- Multi layer Perceptron, parameters and climatic signals in three time scales include short, middle and long term in a rain-gauge station located at south plain of Qazvin Province. Three different scenarios were tested as inputs model. Optimal combination of variables was determinate by Gamma-Test after identification of input variables using cross-correlation. Results showed, influence of climatic signals increased and against the influence of meteorological parameters decreased when time scale were increased from short-term to long-term. MEI (Multivariate ENSO Index) and rainfall were introduced as the most effective climatic signals and meteorological parameter for each scale, respectively. Neural Network modeling which has hidden layer with enough neurons, Sigmoid Function in middle layer and linear function at output layer was used. The most appropriate of the number neurons was determined in each scenario and wasn’t observed significant correlation between increasing or decreasing the error and number of neurons. Finally, the most appropriate network structure was determined based on evaluation indexes in three scenarios and each time scale.
vahid jafarian; Mohammadreza Yazdani; Mohammad Rahimi; Mehdi Ghorbani
Mohammad Reza Yazdani; Ali Asghar zolfaghari
Abstract
Watershed outflow has influenced by different factors such as climatic, human and physical aspects and this Variability of effective factors can cause complex conditions, difficulty of flow forecasting and it mainly originates by different local and temporal scales of these factors. Also, some remote ...
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Watershed outflow has influenced by different factors such as climatic, human and physical aspects and this Variability of effective factors can cause complex conditions, difficulty of flow forecasting and it mainly originates by different local and temporal scales of these factors. Also, some remote meteorological signals can cause changes in meteorological conditions in different regions. Hablehrud river flow has a vital role in regional development, especially for agricultural section. Thus research of river flow forecasting should be done for water resources management especially when there are drought and climate change conditions in order to facilitate sustainable development. In this study four nonlinear models of artificial neural networks including Generalized Feed Foreward Networks (JFNNs), Jordan/Elman Networks(JENs), Time Lag Recurrent Networks(TLRNs) and Radius Basis Function Networks(RBF) was used to modeling Hablehrud river flow(Bonkuh station) during 1982 to 2011. Input variables after sensitivity analysis were used in 4 models and 4 scenarios. Ten teleconnection indexes were used as input of the model to evaluate their roles in model capability. Results indicated that in the test stage Jordan/Elman Networks represented lower error compared with selected models (RMSE for 4 scenarios are5.57, 4.9, 5.35 and 4.62 respectively). In general error showed decreasing trend from first scenario to the last. Error was decreased of 15 to 31 percent by using teleconnection patterns as inputs (GFFN=%26, JEN=%15.8, TLRN=%25.5 and RBF=%31.7). Totally using teleconnection indexes as inputs in the modeling stage can diminish error of flow forecasting, although selected models indicated different results due to its variable topologies.
Mehdi Ghorbani; Vahid Jafarian; Mohammad Reza Yazdani; Mahsa Abdolshahnejad
Abstract
Achieving integrated natural resource management fundamentally needs effective and coordinatedrelationship, collaboration, and synergy among various actors who have common but differentresponsibilities. In this sense, the foundation of comprehensive and integrated management is notcompatible with centralization ...
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Achieving integrated natural resource management fundamentally needs effective and coordinatedrelationship, collaboration, and synergy among various actors who have common but differentresponsibilities. In this sense, the foundation of comprehensive and integrated management is notcompatible with centralization and top-down strategies. The aim of this paper is analysis of networkand organizational cohesion of natural resources stakeholders in Semnan province. In this study,relations of existing organizations within the network have been investigated based on interorganizationalinformation transfer and collaboration through social network analysis method andapplying macro-level and middle indexes of institutional network including; the network size,density, ties reciprocity, and centralization at macro-level and core-periphery index at middle level.Policy monitoring emphasized in present paper’s title refers to this question that how successfullynatural resource integrated management policies have been realized at least within the fourth andfifth development programs. Therefore, present study is an attempt to address this questionquantitatively and relying on the results of indexes of structural analysis of natural resourcestakeholders’ network in the pilot area. The results of this study indicate that institutional cohesionis 40 percent (poor) and sustainability of institutional network based on reciprocity is about 47percent (medium). Additionally the core-periphery index showed that the density of institutionalnetwork of Semnan province in core actors’ subgroup is 77 percent and in periphery actors’subgroup is 25 percent. Research findings identify existing capacities for applyin integrated naturalresources management and reveal the necessity of reducing network centralization andstrengthening the relationship among various stakeholders of this section.
