A practical real option methodology for the evaluation of farm-in/out joint venture agreements in mineral exploration

Although the “real option valuation” (ROV) methodology offers extremely valuable insights in optimising investment decisions in the face of uncertainty, its practical acceptance in the mining industry has until recently been slow because of its perceived computational complexity. Recent conceptual advances in the use of binomial lattices and software developments in the areas of decision trees and dynamic programming, have significantly simplified ROV analysis and made it of practical application in day-to-day financial evaluations and decisions involving uncertainty. This paper provides general background on the ROV methodology and an example of how a typical farm-in/out agreement, as a preliminary to the establishment of a joint venture (JV), can be valued as a series of sequential and compound real options. For illustrative and quality assurance purposes, a simple farm-in/out agreement is valued from the point of view of the party acquiring equity in the project (the farm-inee) using two distinct methods, i.e. (a) a binomial lattice and (b) a decision tree in combination with binomial stochastic processes, in both cases neutralising risk using the user-friendly “risk-neutral probability”. The fact that exactly the same ROV is obtained by both methods provides confidence in the modified decision tree approach, which opens up the capacity to value the more complex sequential/compound real options inherent in real-life farm-in/out agreements. The model is then modified to incorporate a number of realistic contractual conditions often encountered in typical exploration and mining farm-in/out deals. The paper demonstrates how the increased complexity of the model can be relatively easily addressed using a decision tree with dynamic programming capability.     

卤代海因的危险特性实验研究

为评价卤代海因的危险特性,通过克南实验、时间压力实验以及固体氧化性实验分别对二氯海因、溴氯海因以及二溴海因的爆炸性和氧化性进行了测试,通过家兔皮肤刺激性/腐蚀性实验对三种卤代海因的刺激性进行了研究,并分别对三种卤代海因的危险性进行了对比分析。结果表明：二氯海因、溴氯海因以及二溴海因都具有氧化性、对家兔皮肤具有严重刺激性、在正常商业包件中可能达到的压力下点火会导致具有爆炸猛烈性的爆燃;溴氯海因以及二溴海因克南实验极限直径均小于1.0mm,在封闭条件下加热不显示效应,二氯海因的克南实验极限直径为2.0mm,在封闭空间加热显示某种效应。三种卤代海因的氧化性和对家兔皮肤的刺激性没有显著区别,但二氯海因较溴氯海因以及二溴海因在封闭空间加热显示的效应更强。     

矿产资源总体规划对四川省甘孜州资源-环境承载力影响分析研究

本文根据矿区资源环境承载力的内涵,构建了"目标层-准则层-因子层-指标层"资源环境承载力评价体系,并在此基础上通过专家咨询打分的方式,采用层次分析法(AHP法)计算得出甘孜州矿产资源总体规划实施现状年、近景年、远景年3个时间段资源-环境承载力综合指数,为四川省甘孜州矿产资源总体规划环评影响影响评价提供了技术支撑和科学根...     

Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling1

Lin, Zhulu, 2011. Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2010.00513.x Abstract: Newnans, Lochloosa, and Orange Lakes are closely hydrologically connected karst lakes located in north‐central Florida, United States. The complex karst hydrology in this region poses a great challenge to the hydrological modeling that is essential to the development of Total Maximum Daily Loads for these lakes. We used a Hydrological Simulation Program – Fortran model coupled with the parallel Parameter ESTimation model calibration and uncertainty analysis software to estimate effectively the hydrological interactions between the lakes and the underlying upper Floridan aquifer and the water budgets for these three lakes. The net results of the lake‐groundwater interactions in Newnans and Orange Lakes are that both lakes recharge the underlying upper Floridan aquifer, with the recharge rate of the latter one magnitude greater than that of the former. However, for Lochloosa Lake, the net lake‐groundwater interaction is that the lake gains water from groundwater in a significant amount, approximately 40% of its total terrestrial water input. The annual average vertical leakages estimated for Newnans, Lochloosa, and Orange Lakes are 6.0 × 10⁶, ?8.9 × 10⁶, and 44.4 × 10⁶ m³, respectively. The average vertical hydraulic conductance (K_v/b) of the units between a lake bottom and the underlying upper Floridan aquifer in this region are also estimated to be from 1.26 × 10^?4 to 1.01 × 10^?3 day^?1.     

集中空调系统积尘理化特征

利用现场采样与实验分析的方法,对集中空调系统内的积尘进行了粒径分布、水溶性碳物质及离子含量的分析,以评估集中空调系统内积尘对微生物滋生的影响.结果表明,集中空调系统除新风段外的6个采样段,积尘平均粒径介于6—20μm之间,新风段积尘平均粒径为41.30μm;沿送风方向,微粒的平均粒径减小,单位积尘量所含的水溶性离子和有...     

Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

A Perspective on Nonstationarity and Water Management1

Hirsch, Robert M., 2011. A Perspective on Nonstationarity and Water Management. Journal of the American Water Resources Association (JAWRA) 47(3):436‐446. DOI: 10.1111/j.1752‐1688.2011.00539.x Abstract: This essay offers some perspectives on climate‐related nonstationarity and water resources. Hydrologists must not lose sight of the many sources of nonstationarity, recognizing that many of them may be of much greater magnitude than those that may arise from climate change. It is paradoxical that statistical and deterministic approaches give us better insights about changes in mean conditions than about the tails of probability distributions, and yet the tails are very important to water management. Another paradox is that it is difficult to distinguish between long‐term hydrologic persistence and trend. Using very long hydrologic records is helpful in mitigating this problem, but does not guarantee success. Empirical approaches, using long‐term hydrologic records, should be an important part of the portfolio of research being applied to understand the hydrologic response to climate change. An example presented here shows very mixed results for trends in the size of the annual floods, with some strong clusters of positive trends and a strong cluster of negative trends. The potential for nonstationarity highlights the importance of the continuity of hydrologic records, the need for repeated analysis of the data as the time series grow, and the need for a well‐trained cadre of scientists and engineers, ready to interpret the data and use those analyses to help adjust the management of our water resources.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.