Erosion of geological units and sediment load in rivers can be considered as the serious problems in recent decades.Increasing sediment loads generate major hazards for water resources development,particularly in terms of loss of reservoir storage due to sedimentation and siltation of water distribution systems.In this paper,the performance of four sediment rating curve (SRC) development methods was evaluated for the Shirin Darreh River(SDR) basin (1750 km2),located in North Khorasan Province,Iran.Data of flow discharge (Q) and suspended sediment flux (SSF)(Q-SSF pairs,N=957)and daily flow discharge,recorded by the Regional Water Company of North Khorasan (RWCNK) at the Qaleh-Barbar (QB) gauging site during 1989-2018were used.The flow discharge classification method performed best by meeting the desired criteria of most statistical indices,including normalized root mean square error (NRMSE),mean bias error (MBE),mean absolute error (MAE),index of agreement (d),and coefficient of determination (R~2).Based on the optimized method,the rate of suspended sediment transportation at the study site was estimated about2.7×10~6 ton year~(-1).Erodibility of the exposed formations in the study area was estimated based on a factorial scoring model (FSM).Three indices,focused on the outcrop and erodibility,were calculated for the geological units at sub-basin and total scales.Marl deposits are the most extensive geological unit in the three sub-basins and the maximum formation outcrop ratio (FOR) and participation in erosion (PCE)were obtained for these rocks at total scale.In fact,marl unit can be regarded as the main source to supply the suspended sediments in the study basin. 相似文献
Groundwater over-exploitation has been increasing in Iran. Competing demands have grown in the face of perennial water shortages, a situation which has been exacerbated by drought conditions in the past decade. This paper describes the strategy development process recently undertaken in South Khorasan, Iran, in which the inclusion of stakeholder views was central to the approach. It involved government officials and various public and private sector interest groups. Particular efforts were made to involve well irrigators, who are likely to be heavily impacted by changes required to reduce groundwater pumping to a sustainable level. The paper concludes with a discussion of lessons learned. 相似文献
Despite advanced development in computational techniques, the issue of how to adequately calibrate and minimize misfit between system properties and corresponding measurements remains a challenging task in groundwater modeling. Two important features of the groundwater regime, hydraulic conductivity (k) and specific yield (Sy), that control aquifer dynamic vary spatially within an aquifer system due to geologic heterogeneity. This paper provides the first attempt in using an advanced swarm-intelligence-based optimization algorithm (cuckoo optimization algorithm, COA) coupled with a distributed hydrogeology model (i.e., MODFLOW) to calibrate aquifer hydrodynamic parameters (Sy and k) over an arid groundwater system in east Iran. Our optimization approach was posed in a single-objective manner by the trade-off between sum of absolute error and the adherent swarm optimization approach. The COA optimization algorithm further yielded both hydraulic conductivity and specific yield parameters with high performance and the least error. Estimation of depth to water table revealed skillful prediction for a set of cells located at the middle of the aquifer system whereas showed unskillful prediction at the headwater due to frequent water storage changes at the inflow boundary. Groundwater depth reduced from east toward west and southwest parts of the aquifer because of extensive pumping activities that caused a smoothening influence on the shape of the simulated head curve. The results demonstrated a clear need to optimize arid aquifer parameters and to compute groundwater response across an arid region. 相似文献
This study attempted to examine the effects of biochar amendment together with bio-fertilizer on soybean yield and its qualitative properties, as well as a few chemical properties of soil through a factorial randomized complete block design at three replications in east of Golestan Province (Iran) during 2014. The two factors under study included the following: (1) biochar amendment (in four levels of 0, 2.5, 8, and 16 tons per hectare), (2) bio-fertilizer containing phosphorus and sulfur growth-promoting rhizobacteria (in two levels of inoculation and non-inoculation) applied through foliar feeding. The results of analysis of variance indicated that interactions of biochar amendment and bio-fertilizer on harvest index and grain yield were significant (p ≤?0.01). According to the results of this study, the highest harvest index and oil content were 56.9, and 17.7%, respectively, in the treatment of 8 tons per hectare biochar and inoculation with bio-fertilizer. The lowest harvest index and the lowest oil content were in the control treatment. The interaction of biochar and bio-fertilizer on bulk density and cation exchange capacity was significant (p ≤?0.01). The results of this study demonstrated that biochar affected the amount of residual nitrogen in the soil after harvest, cation exchange capacity (CEC), acidity (pH), and electrical conductivity (EC). The highest grain yield (3440 kg/ha) was in the 8-ton biochar treatment with inoculated bio-fertilizer. Our study concludes that the biochar and bio-fertilizers can improve grain yield of soybean till 51% relative to the control. 相似文献
Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images. 相似文献
Theoretical and Applied Climatology - This study seeks to investigate the effect of topographic (slope, elevation, and aspect) and climatic (precipitation and temperature) factors on vegetation in... 相似文献
The compression index (Cc), which is used to calculate the consolidation settlement of fine-grained soils, can be determined through consolidation testing. Given that exploring the soil in a local region is highly important to determine the correlation between the Cc and other soil indices, the present study investigated these correlations in undisturbed and disturbed samples through 130 consolidation tests and determining the Cc of Tehran clay. The results are suggestive of the validity of the linear correlation between the Cc and the unit weight and initial void ratio of the soil, with several relations presented to estimate the Cc of Tehran clay soil. In contrast, the initial water content, liquid limit and the plasticity index do not produce reliable correlations with the Cc of the local clay soil, and a relation based on these index parameters cannot be recommended in this area. Further, the presented empirical correlations were compared with the existing ones. More over time-displacement and e-log σ’ graphs for undisturbed and disturbed samples are compared and stress history of the site are presented. The results are significant in terms of engineering applications, saving time and money and provides an initial estimation of compression index.
ABSTRACT Since piles are one of the major geotechnical foundation systems, estimation of their axial bearing capacity is of great importance. Employing different design methods, resulting in a wide range of bearing capacity estimations, complicates the selection of an appropriate design scheme and confirms the existence of model error along with the inherent soil variability in bearing capacity prediction. This paper tends to evaluate different predictive methods in Reliability-Based Design (RBD) framework. In this regard, different static analyses, SPT and CPT-based methods are considered to evaluate which approaches collectively and which method individually, have more reliable predictions for compiled data bank. In order to assess reliability indices and resistance factors, two approaches have been considered, i.e. First Order Second Moment method (FOSM) and First Order Reliability Method (FORM). To investigate the reliability indices for different methods in both RBD approaches, various safety factors and loading ratios have been considered. Also, the Load and Resistance Factor Design (LRFD) resistance factors are calibrated for different target reliability indices and loading ratios. Results show that CPT-based methods are more reliable among other methods. Furthermore, the estimated efficiency ratio, i.e. the ratio of resistance factor to resistance bias factor, confirms this agreement. 相似文献