Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study     

Najmeh?Khalili  Saeed?Reza?KhodashenasEmail author  Kamran?Davary  Mohammad?Mousavi?Baygi  Fatemeh?Karimaldini 《Arabian Journal of Geosciences》2016,9(13):624

In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M₅₃₁ and M₇₄₁, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models.  相似文献   

Evaluating the support vector machine for suspended sediment load forecasting based on gamma test   总被引：1，自引：0，他引：1  

Sharareh Rashidi  Mehdi Vafakhah  Elham Kakaei Lafdani  Mohammad Reza Javadi 《Arabian Journal of Geosciences》2016,9(11):583

Due to the various influencing factors on river suspended sediment transportation, determining an appropriate input combination for developing the suspended sediment load forecasting model is very important for water resources management. The influence of pre-processing of input variables by Gamma Test (GT) was investigated on performance of Support Vector Machine (SVM) with two kernels; Radial Basis Function (RBF) and polynomial in order to forecast daily suspended sediment amount in the period between 1983 and 2014 at Korkorsar basin, northern Iran. The best input combination was identified using GT and correlation coefficient analysis. Then, the SVM model was developed and the suspended sediment amount was forecasted with RBF and polynomial kernels. The obtained results in testing phase showed that GT-SVM (RBF kernel) model can estimate suspended sediment more accurately with the lowest RMSE (14.045 ton/day), highest correlation coefficient (0.88) and highest NSEC coefficient (0.88) than SVM (RBF kernel) model (RMSE?=?18.36ton/day, \( {R}^2=0.79, \) \( NSEC=0.73 \)) and had a better performance than the other models. The results indicated that in forecasting the first nine maximum values of suspended sediment load, GT-SVM (RBF) had a higher capability than the other models and could provide a more accurate estimation from the maximum rate of suspended sediment. The results of this study showed the capability of identifying the priority of the input parameters can change GT to a useful and technical test for input variables pre-processing to forecast the amount of suspended sediments.  相似文献   

Storage dam’s locality placing by MCDM techniques (case study: three dams in Iran)     

Saeed Reza Khodashenas  Niloufar Yarahmadi 《Arabian Journal of Geosciences》2016,9(13):612

MCDM (multi-criteria decision making) techniques are used to choose the best alternative among the relevant ones and rank the others. In this research, MCDM techniques were used to choose and rank the best places for constructing storage dams in Iran. To achieve this goal, the relevant information and data about dam construction situations were collected. Then, the recommended places for constructing storage dams were ranked by using MCDM techniques and according to the most suitable criteria which have been chosen based on experts’ opinions. To rank dam constructing project, three MCDM techniques, i.e., TOPSIS, AHP, and DEMATEL, were used. The results showed that the application of MCDM models by putting emphasis on economic, social, political, and technical criteria enables government and watershed managers to choose the best alternative(s) for constructing a storage dam.  相似文献   

Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province,Iran     

Omid Rahmati  Hamid Reza Pourghasemi  Hossein Zeinivand 《国际地球制图》2016,31(1):42-70

Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main goal of this study was to investigate the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran. At first, a flood inventory map was prepared using Iranian Water Resources Department and extensive field surveys. In total, 144 flood locations were identified in the study area. Of these, 101 (70%) floods were randomly selected as training data and the remaining 43 (30%) cases were used for the validation purposes. In the next step, flood conditioning factors such as lithology, land-use, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index (TWI) and altitude were prepared from the spatial database. Subsequently, the receiver operating characteristic (ROC) curves were drawn for produced flood susceptibility maps and the area under the curves (AUCs) was computed. The final results indicated that the FR (AUC = 76.47%) and WofE (AUC = 74.74%) models have almost similar and reasonable results. Therefore, these flood susceptibility maps can be useful for researchers and planner in flood mitigation strategies.  相似文献   

Luminescence dating of buried cobble surfaces from sandy beach ridges: a case study from Denmark     

Priscila E. Souza  Reza Sohbati  Andrew S. Murray  Aart Kroon  Lars B. Clemmensen  Mikkel U. Hede  Lars Nielsen 《Boreas: An International Journal of Quaternary Research》2019,48(4):841-855

Here we investigate the use of optically stimulated luminescence (OSL) for dating cobbles from the body of successive beach ridges and compare cobble surface‐derived ages to standard quartz OSL ages from sand. Between four and eight cobbles and sand samples (age control) were dated with the luminescence method, taken from the modern beach and from beach ridges on the south and north extremes of a prograding spit on the westernmost coast of Lolland, Denmark. Luminescence‐depth profiles perpendicular to the surfaces of the cobbles show that the feldspar infrared signals stimulated at 50 °C were fully reset to various depths into the cobbles prior to final deposition; as a result, the equivalent doses determined from close to the surface of such cobbles can be used to calculate burial ages. Beach‐ridge burial ages given by the average of ages of individual cobbles taken from the same site are consistent, within errors, with the ages derived from the sand samples. Cobble‐ and sand‐derived ages show that the southernmost beach ridge at Albuen was formed around 2 ka ago, indicating that this sandy spit is younger than other coastal systems in Denmark. The agreement between ages derived from clasts and from standard quartz OSL in this study confirms that, even in the absence of sandy sediments, we can reliably date sites using OSL by targeting larger clasts. In addition, the record of prior light exposure contained in the shape of the cobbles’ luminescence‐depth profile removes one of the major uncertainties (i.e. the degree of signal reset prior to burial) in the luminescence dating of high latitude sites.  相似文献   

Simulating precipitation in the Northeast United States using a climate-informed K-nearest neighbour algorithm     

Saman Armal  Naresh Devineni  Nir Y. Krakauer  Reza Khanbilvardi 《水文研究》2020,34(20):3966-3980

Decadal prediction using climate models faces long-standing challenges. While global climate models may reproduce long-term shifts in climate due to external forcing, in the near term, they often fail to accurately simulate interannual climate variability, as well as seasonal variability, wet and dry spells, and persistence, which are essential for water resources management. We developed a new climate-informed K-nearest neighbour (K-NN)-based stochastic modelling approach to capture the long-term trend and variability while replicating intra-annual statistics. The climate-informed K-NN stochastic model utilizes historical data along with climate state information to provide improved simulations of weather for near-term regional projections. Daily precipitation and temperature simulations are based on analogue weather days that belong to years similar to the current year's climate state. The climate-informed K-NN stochastic model is tested using 53 weather stations in the Northeast United States with an evident monotonic trend in annual precipitation. The model is also compared to the original K-NN weather generator and ISIMIP-2b GFDL general circulation model bias-corrected output in a cross-validation mode. Results indicate that the climate-informed K-NN model provides improved simulations for dry and wet regimes, and better uncertainty bounds for annual average precipitation. The model also replicates the within-year rainfall statistics. For the 1961–1970 dry regime, the model captures annual average precipitation and the intra-annual coefficient of variation. For the 2005–2014 wet regime, the model replicates the monotonic trend and daily persistence in precipitation. These improved modelled precipitation time series can be used for accurately simulating near-term streamflow, which in turn can be used for short-term water resources planning and management.  相似文献   

Assessing factors affecting drought,earthquake, and flood risk perception: empirical evidence from Bangladesh     

Mallick  Javed  Salam  Roquia  Amin  Ruhul  Islam  Abu Reza Md. Towfiqul  Islam  Aznarul  Siddik  Md. Nur Alam  Alam  G. M. Monirul 《Natural Hazards》2022,112(2):1633-1656

Natural Hazards - Understanding household disaster risk perception is crucial to formulate and apply disaster risk reduction strategies. Using survey data from 300 households from three highly...  相似文献   

Compounding effects of human activities and climatic changes on surface water availability in Iran     

Ashraf  Samaneh  AghaKouchak  Amir  Nazemi  Ali  Mirchi  Ali  Sadegh  Mojtaba  Moftakhari  Hamed R.  Hassanzadeh  Elmira  Miao  Chi-Yuan  Madani  Kaveh  Mousavi Baygi  Mohammad  Anjileli  Hassan  Arab  Davood Reza  Norouzi  Hamid  Mazdiyasni  Omid  Azarderakhsh  Marzi  Alborzi  Aneseh  Tourian  Mohammad J.  Mehran  Ali  Farahmand  Alireza  Mallakpour  Iman 《Climatic change》2019,152(3-4):379-391

Climatic Change - By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change...  相似文献   

Simultaneous adoption of risk management strategies to manage the catastrophic risk of maize farmers in Bangladesh     

Adnan  K. M. Mehedi  Ying  Liu  Sarker  Swati Anindita  Yu  Man  Eliw  Moataz  Sultanuzzaman  Md. Reza  Huq  Md. Enamul 《GeoJournal》2021,86(4):1981-1998

GeoJournal - Risk and uncertainty are distinctive features of agricultural cultivation, which significantly affect the production and income. Risk management is an important way for farmers to...  相似文献   

Sedimentological,Geochemical and Hydrogeochemical Studies of Alluvial Fans for Mineral and Environmental Purposes (Case Study of Southwestern Iran)     

Saeid Pourmorad  Harami  Reza Mousavi  Solgi  Ali  Aleali  Mohsen 《Lithology and Mineral Resources》2021,56(1):89-112

Lithology and Mineral Resources - The alluvial-fan sediments play a very important role in mineral reserves and underground water resources, though a comprehensive study on such sediments,...  相似文献