Reliability framework for characterizing heat wave and cold spell events

Natural Hazards - Extreme weather events such as heat waves and cold spells affect people’s lives. This study develops a probabilistic framework to evaluate heat waves and cold spells. As...     

Evaluation of long term trends in apple cultivation and its productivity in Jammu and Kashmir from 1975 to 2015

GeoJournal - Horticulture plays a pivotal role in the economy of Jammu and Kashmir. Owing to favourable agro-climatic conditions, temperate horticulture is fast expanding in the state which is...     

Equatorial radius of the Earth: A dynamical determination

An intrresting variation on the familiar method of determining the earth's equatorial radius a_e, from a knowledge of the earth's equatorial gravity is suggested. The value of equatorial radius thus found is 6378,142±5 meters. The associated parameters are GM=3.986005±.000004 × 10²⁰ cm³ sec-⁻² which excludes the relative mass of atmosphere ≅10⁻⁶ ξ GM, the equatorial gravity γ_e 978,030.9 milligals (constrained in this solution by the Potsdam Correction of 13.67 milligals as the Potsdam Correction is more directly, orless indirectly, measurable than the equatorial gravity) and an ellipsoidal flattening of f=1/298.255.     

Socio-hydrological framework for investigating farmers’ activities affecting the shrinkage of Urmia Lake; hybrid data mining and agent-based modelling

ABSTRACT

Developing a general framework to capture the complexities associated with the non-linear and adaptive nature of farmers facing water resources scarcity is a challenging problem. This paper integrates agent-based modelling (ABM) and a data mining method to develop a hybrid socio-hydrological framework to provide future insights for policy-makers. The data associated with the farmers’ main characteristics were collected through field surveys and interviews. Afterwards, the association rule was employed to discover the main patterns representing the farmers’ agricultural decisions. The discovered patterns were then used as the behavioural rules in ABM to simulate the agricultural activities. The proposed framework has been was applied to explore the interactions between agricultural activities and the main river feeding the Urmia-Lake, Iran. The outcomes indicate that farmers’ acquisitive traits and belongings have significant impacts on their socio-hydrological interactions. The reported values of the efficiency criteria may support the satisfactory performance of the proposed framework.     

Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.     

Statistical analysis of short-term water stress conditions at Riggs Creek OzFlux tower site

Theoretical and Applied Climatology - A large range of indices and proxies are available to describe the water stress conditions of an area subject to different applications, which have varying...     

Optimal Location of Wells for Storage and Recovery of Surplus Desalinated Water in Coastal Aquifers

Storage of water in aquifers using injection wells is an efficient way for utilizing excess desalinated water in arid regions. In this investigation we estimate the benefits of optimally recharging seasonal surplus desalinated water into a strategic coastal aquifer already benefitting from natural recharge of flash-floods water by a recharge dam. Since, usually the buyers of desalinated water commit to purchase surplus desalinated water under take-or-pay contracts, any attempt in utilizing the paid water is beneficial. Coastal cities are observing an increased urbanization leaving limited space for aquifer recharge infrastructure. In order to determine the optimal location of wells and maximize the use of surplus desalinated water available in winter period, a decision tool combining a numerical groundwater flow simulation model (MODFLOW) with an optimization model is developed. The results of this study show that increasing the number of wells from the existing 45 wells to 173 would allow storing 31.4 million cubic meter per year of excess desalinated water into the aquifer that can be used during later during summer months. The net benefit would reach US$55 million/year while the cost of drilling the new wells is US$5.11 million.     

Spatiotemporal changes in precipitation concentration over Iran during 1962–2019

Climatic Change - Changes in precipitation pattern can lead to widespread impacts across natural and human systems. This study assesses precipitation variability as well as anthropogenic and...     

An investigation of near surface wind speed trends in arid and semiarid regions of Iran

Wind plays an important role on the ecosystems and hydrological cycles besides other meteorological parameters such as temperature, precipitation, sunshine, and relative humidity. It strongly affects evapotranspiration, especially in arid and semiarid regions where there are serious problems in regard to water resource management. Evaluating the wind speed trend can provide good information for future agricultural planning. This study was conducted in order to investigate the wind speed trends over 24 synoptic meteorological stations located in arid and semiarid regions of Iran from 1975 to 2005. Near-surface wind speed was trended by nonparametric Mann–Kendall test spatially and temporally in three time scales (annual, seasonal, and monthly). Then, Sen’s slope estimator was used to determine the amount of the changes; furthermore, 10-year moving average low-pass filter was applied to show general trends. Finally, the smoothed time series derived from the mentioned filter were classified in three clusters for each time series and then mapped to show their spatial distribution pattern. Results showed insignificant and significant, increasing and decreasing trends during the surveyed time. Wind speeds in less than 50 % of stations changed statistically in all time scales, and in most cases, the frequency of the upward trends was more than that of downward ones. The spatial distribution of significant wind speed showed that the increase mostly occurred in eastern part. Clustering gave us the turning point around 1990. Clearly, when clusters were mapped, they indicated the same pattern as the Z value maps derived from Mann–Kendall test which meant that the outputs of the mentioned method confirmed the other one. As the wind speed trends in different stations likely to follow the previous evapotranspiration (ET₀) trend results in Iran, it confirms that wind speed was an effective parameter on ET₀, even though other parameters should be considered too.     

Synoptic analysis of dust storms in the Middle East

Dust storm in the Middle East and south-west Asia is a natural hazard and the Tigris-Euphrates alluvial plain has been recognized as the main dust source in this area. In this study, more than 60 dust storms that occurred during the period 2003–2011 are investigated on the basis of MODIS satellite images, and 12 of the dust storms are selected for synoptic analysis using the NCEP-NCAR Reanalysis Data. The potential dust sources in the Middle East and south-west Asian region (20°E to 80°E, 5°N to 50°N) are analyzed and used in the synoptic analysis. Dust storms in the region can be grouped into two main categories, i.e., the Shamal dust storms and the frontal dust storms. Synoptic systems, associated with the two categories, are distinguished and the frequency of the patterns is identified. For 68% of the Shamal dust storms, a high pressure system is situated between 0°E to 30°E and 27°N to 45°N, and a low pressure system between 50°E to 70°E and 23°N to 43°N. For 86% of the frontal dust storms, a high is located between 51°E to 67°E and 18°N to 33°N and a low between 28°E to 48°E and 32°N to 43°N. Three main patterns for Shamal dust storms are identified, which represent about 60% of the Shamal dust storms. This analysis confirms that the Shamal is related to the anticyclones located over northern Africa to Eastern Europe and the monsoon trough over Iraq, southern Iran, Pakistan and the Indian Subcontinent. The analysis also shows that the main dust sink for the frontal dust storms in Tigris and Euphrates alluvial plain extends from center of Iraq to west and center of Iran and, in most severe cases, to northern Iran and the southern coast of the Caspian Sea.