Evaluation of CRU-JRA gridded meteorological dataset for modeling of wheat production systems in Iran.

Meteorological variables are essential inputs for agricultural simulation models and the lack of measured data is a big challenge for the application of these models in many agricultural zones. Studies indicated that gridded meteorological datasets can be proper replacements for measured data. This paper aimed to examine a new gridded meteorological dataset namely CRU-JRA for crop modeling intents. The CRU-JRA is a 6-hourly dataset with a spatial resolution of 0.5° × 0.5° that was primarily constructed for modeling purposes. The CERES-Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulation of irrigated and rainfed wheat production systems in Iran. Results showed that the CRU-JRA maximum and minimum temperature values had a relatively fine accuracy with a normalized root mean square error (NRMSE) of 14% for the simulated grain yield. The performance of the CRU-JRA solar radiation values for the simulation of grain yield was similar with a NRMSE of 14.4%. The weakest performance was found for the CRU-JRA precipitation values with a NRMSE of 18.9%. Overall, the CRU-JRA dataset performed comparatively acceptable and similar to existing gridded meteorological datasets for crop modeling purposes in the study area, however further calibrations can improve the accuracy of the next versions of this dataset. More research is necessary for the investigation of the CRU-JRA dataset for agricultural modeling purposes across diverse climates.

Analyzing trends of days with low atmospheric visibility in Iran during 1968-2013.

Atmospheric visibility (AV) is an indicator for assessing air quality and is measured in standard weather stations. The AV can change as a result of two main factors: air pollution and atmospheric humidity. This study aimed to investigate trends in the number of days with AV equal or less than 2 km (DAV2) in Iran during 1968-2013. Consequently, 43 weather stations with different climates were evaluated across the country, using the Mann-Kendall (MK) trend test. The results show that the number of stations with positive (i.e., significant or non-significant) MK z values was equal to, or greater than, those with negative MK z values, in all months and seasons of the year, as well as annually. Furthermore, summer and autumn had, respectively, the least and most stations with positive MK z values. Fewer trends in DAV2 were detected in the central, east, and northeast regions of the country. Analyzing the DAV2 and relative humidity together indicated that over 30% of stations had at-risk air quality in January, and that the largest number of stations with at-risk air quality was in the autumn and winter. These results are useful for better environmental planning to improve air quality, especially in developing countries such as Iran, where reduced air quality has been a major problem in recent decades.

Medical History and Preoperative Coagulation Profile as Predictors of Outcomes in Elective Spinal Surgery: A Meta-Analysis.

BACKGROUND: In patients with unremarkable medical history, comprehensive preoperative hemostasis screening in elective neurosurgery remains debated. Comprehensive medical history has shown to be noninferior to coagulation profile to evaluate surgical outcomes. This study aims to evaluate the predictiveness of preoperative coagulation screening and medical history for surgical outcomes. METHODS: Databases were searched until April 2023 for observational cohort studies that reported preoperative hemostasis screening and clinical history prior to elective neurosurgical procedures. Outcomes of interest included postoperative transfusion, mortality, and complications. Pooled relative risk ratios (RRs) were analyzed using random-effects models. RESULTS: Out of 604 studies, 3 cohort studies met our inclusion criteria, adding a patient population of 83,076. Prolonged partial thromboplastin time (PTT; RR=1.42, 95% confidence interval [CI] =1.14, 1.77, P=0.002), elevated international normalized ratio (INR; RR=2.01, 95% CI=1.14, 3.55, P=0.02), low platelet count (RR=1.58, 95% CI=1.34, 1.86, P<0.00001), and positive bleeding history (RR=2.14, 95% CI=1.16, 3.93, P=0.01) were associated with postoperative transfusion risk. High PTT (RR=2.42, 95% CI=1.24, 4.73, P=0.010), High INR (RR=8.15, 95% CI=5.97, 11.13; P<0.00001), low platelet count (RR=4.89, 95% CI=3.73, 6.41, P<0.00001), and bleeding history (RR=7.59, 95% CI=5.84, 9.86, P<0.00001) were predictive of mortality. Prolonged PTT (RR=1.53, 95% CI=1.25, 1.86, P=<0.0001), a high INR (RR=3.41, 95% CI=2.63, 4.42, P=< 0.00001), low platelets (RR=1.63, 95% CI=1.40, 1.90, P=<0.00001), and medical history (RR=2.15, 95% CI=1.71, 2.71, P=<0.00001) were predictive of complications. CONCLUSIONS: Medical history was a noninferior predictor to coagulation profile for postoperative transfusion, mortality, and complications. However, our findings are mostly representative of elective spinal procedures. Cost-effective alternatives should be explored to promote affordable patient care in patients with unremarkable history.

Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System.

So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i) having a discrete nature; and (ii) working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance) of the state variable (water level in the reservoir) is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP), and a discrete stochastic dynamic game model (PSDNG). By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in water allocation in situations of water scarcity properly. Also, comparing the annual dynamic game models, the presented models result in superior results in practice. Furthermore, unlike discrete dynamic game models, the presented models can significantly reduce the runtime thereby avoiding dimensionality problems.

Evaluating nutrient impacts in urban watersheds: challenges and research opportunities.

This literature review focuses on the prevalence of nitrogen and phosphorus in urban environments and the complex relationships between land use and water quality. Extensive research in urban watersheds has broadened our knowledge about point and non-point pollutant sources, but the fate of nutrients is not completely understood. For example, it is not known how long-term nutrient cycling processes in turfgrass landscapes influence nitrogen retention rates or the relative atmospheric contribution to urban nitrogen exports. The effect of prolonged reclaimed water irrigation is also unknown. Stable isotopes have been used to trace pollutants, but distinguishing sources (e.g., fertilizers, wastewater, etc.) can be difficult. Identifying pollutant sources may aid our understanding of harmful algal blooms because the extent of the relationship between urban nutrient sources and algal blooms is unclear. Further research on the delivery and fate of nutrients within urban watersheds is needed to address manageable water quality impacts.

Do tropical cyclones shape shorebird habitat patterns? Biogeoclimatology of snowy plovers in Florida.

BACKGROUND: The Gulf coastal ecosystems in Florida are foci of the highest species richness of imperiled shoreline dependent birds in the USA. However environmental processes that affect their macroecological patterns, like occupancy and abundance, are not well unraveled. In Florida the Snowy Plover (Charadrius alexandrinus nivosus) is resident along northern and western white sandy estuarine/ocean beaches and is considered a state-threatened species. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that favorable nesting areas along the Florida Gulf coastline are located in regions impacted relatively more frequently by tropical cyclones. The odds of Snowy Plover nesting in these areas during the spring following a tropical cyclone impact are seven times higher compared to the odds during the spring following a season without a cyclone. The only intensity of a tropical cyclone does not appear to be a significant factor affecting breeding populations. CONCLUSIONS/SIGNIFICANCE: Nevertheless a future climate scenario featuring fewer, but more extreme cyclones could result in a decrease in the breeding Snowy Plover population and its breeding range. This is because the spatio-temporal frequency of cyclone events was found to significantly affect nest abundance. Due to the similar geographic range and habitat suitability, and no decrease in nest abundance of other shorebirds in Florida after the cyclone season, our results suggest a common bioclimatic feedback between shorebird abundance and tropical cyclones in breeding areas which are affected by cyclones.