Space-time mapping of soil salinity using probabilistic bayesian maximum entropy

The mapping of saline soils is the first task before any reclamation effort. Reclamation is based on the knowledge of soil salinity in space and how it evolves with time. Soil salinity is traditionally determined by soil sampling and laboratory analysis. Recently, it became possible to complement these hard data with soft secondary data made available using field sensors like electrode probes. In this study, we had two data sets. The first includes measurements of field salinity (EC_a) at 413 locations and 19 time instants. The second, which is a subset of the first (13 to 20 locations), contains, in addition to EC_a, salinity determined in the laboratory (EC_2.5). Based on a procedure of cross-validation, we compared the prediction performance in the space-time domain of 3 methods: kriging using either only hard data (HK) or hard and mid interval soft data (HMIK), and Bayesian maximum entropy (BME) using probabilistic soft data. We found that BME was less biased, more accurate and giving estimates, which were better correlated with the observed values than the two kriging techniques. In addition, BME allowed one to delineate with better detail saline from non-saline areas.     

Comparison of hydraulic geometry between sand‐ and gravel‐bed rivers in relation to channel pattern discrimination

A comparison has been made between the hydraulic geometry of sand‐ and gravel‐bed rivers, based on data from alluvial rivers around the world. The results indicate a signi?cant difference in hydraulic geometry among sand‐ and gravel‐bed rivers with different channel patterns. On this basis, some diagrams for discrimination of meandering and braided channel patterns have been established. The relationships between channel width and water discharge, between channel depth and water discharge, between width–depth ratio and water discharge and between channel slope and water discharge can all be used for channel pattern discrimination. The relationship between channel width and channel depth can also be used for channel pattern discrimination. However, the accuracy of these relationships for channel pattern discrimination varies, and the depth–discharge relationship is a better discriminator of pattern type than the classic slope–discharge function. The cause for this difference has been explained qualitatively. To predict the development of channel patterns under different natural conditions, the pattern discriminator should be searched on the basis of independent or at least semi‐independent variables. The relationship between stream power and bed material grain size can be used to discriminate channel patterns, which shows a better result than the discriminator using the slope–discharge relationship. Copyright © 2004 John Wiley & Sons, Ltd.     

夏季降水量与气温资料的恢复试验

该文对我国汛期降水量和气温缺测资料及资料均一性恢复的方法进行试验研究。对单个气候地区（东北区），以及全国6个气候地区用逐步回归和逐步判别方法进行缺测1～5年恢复试验。对东北地区内所有站点的试验表明，逐步判别分析方法比逐步回归分析方法恢复效果好些；选择邻站用判别分析方法建立的恢复模型，效果更好。全国气候地区试验表明，选择邻站的判别分析方法有较好的恢复效果。     

淮河息县站流量概率预报模型研究

应用美国天气局采用的由Roman Krzysztofowicz开发的贝叶斯统计理论建立概率水文预报理论框架，即以分布函数形式定量地描述水文预报不确定度，研究了淮河息县站流量概率预报模型。理论和经验表明，概率预报至少与确定性预报一样有价值，特别当预报不确定度较大时，概率预报比现行确定性预报具有更高的经济价值。     

Determining the maximum degree of harmonic coefficients in geopotential models by Monte Carlo methods

Random errors for the harmonic coefficients of a geopotential model are generated from the matrix of normal equations by a parallel computer applying the Gibbs sampler. This leads to random values for the harmonic coefficients. They are transformed by nonlinear, quadratic transformations to random values for the square roots of degree variances, of mean squares of geoid undulations and gravity anomalies. The expected values of these quantities are not equal to the values of these quantities computed by the estimated harmonic coefficients, due to correlations and errors in the estimation. By hypothesis tests estimated harmonic coefficients distorted by correlations and errors are detected. Applying the tests to the geopotential model ITG-CHAMP01 of the Institute of Theoretical Geodesy in Bonn it is concluded that above the degree 62 the harmonic coefficients cannot add any information to the geopotential model.     

沙坡头没蒿和柠条叶片δ13C 和 N 含量的季节变化特征

通过对腾格里沙漠东南缘沙坡头人工固沙区油蒿和柠条叶片稳定碳同位素分辨率（△）和N 含量的测定，研究了不同种植方式下油蒿和柠条叶片△ 和 N 含量的季节变化及其关系。结果表明：在不同种植方式下，两种植物的△ 与 N 含量在不同月份之间均存在显著差异。油蒿叶片 △ 极显著高于柠条的：在不同种植方式下，油蒿单种下 △ 显著高于混种，柠条则反之。 油蒿叶片 N 含量极显著低于柠条的：不同种植方式下柠条叶片 N 含量无显著差异，而单种油蒿叶片 N 含量则显著低于混种。在 △ 与 N 含量的关系中，柠条叶片 △ 与 N 在两种生境、单种和混种下均极显著正相关，雨明柠条叶片 N 含量可以作为其 △ 与 N 含量的季节变化及其关系在不同微生境有所差异。     

Estimation of daily stream water temperatures with a Bayesian regression approach

Stream water temperature plays a significant role in aquatic ecosystems where it controls many important biological and physical processes. Reliable estimates of water temperature at the daily time step are critical in managing water resources. We developed a parsimonious piecewise Bayesian model for estimating daily stream water temperatures that account for temporal autocorrelation and both linear and nonlinear relationships with air temperature and discharge. The model was tested at 8 climatically different basins of the USA and at 34 sites within the mountainous Boise River Basin (Idaho, USA). The results show that the proposed model is robust with an average root mean square error of 1.25 °C and Nash–Sutcliffe coefficient of 0.92 over a 2‐year period. Our approach can be used to predict historic daily stream water temperatures in any location using observed daily stream temperature and regional air temperature data.     

Characterisation of hydroclimatological trends and variability in the Lake Naivasha basin,Kenya

Recent hydro‐climatological trends and variability characteristics were investigated for the Lake Naivasha basin with the aim of understanding the changes in water balance components and their evolution over the past 50 years. Using a Bayesian change point analysis and modified Mann–Kendall tests, time series of annual mean, maximum, minimum, and seasonal precipitation and flow, as well as annual mean lake volumes, were analysed for the period 1960–2010 to uncover possible abrupt shifts and gradual trends. Double cumulative curve analysis was used to investigate the changes in hydrological response attributable to either human influence or climatic variability. The results indicate a significant decline in lake volumes at a mean rate of 9.35 × 10⁶ m³ year^?1. Most of the river gauging stations showed no evidence of trends in the annual mean and maximum flows as well as seasonal flows. Annual minimum flows, however, showed abrupt shifts and significant (upward/downward) trends at the main outlet stations. Precipitation in the basin showed no evidence of abrupt shifts, but a few stations showed gradual decline. The observed changes in precipitation could not explain the decline in both minimum flows and lake volumes. The findings show no evidence of any impact of climate change for the Lake Naivasha basin over the past 50 years. This implies that other factors, such as changes in land cover and infrastructure development, have been responsible for the observed changes in streamflow and lake volumes. Copyright © 2015 John Wiley & Sons, Ltd.     

中国沿海小黄鱼种群动力学及其空间异质性研究

小黄鱼是我国近海四种最重要的经济鱼类之一，在过去的几十年中小黄鱼种群及其两个地理亚种群经历了巨大的变化。小黄鱼的种群动力学研究，对于维持这一重要渔业的可持续管理是至关重要的。目前仅有的两个小黄鱼种群动力学模型只涵盖了较短的时间，且没有关注其空间差异。本文研究了1968年至2015年间黄渤海和东海小黄鱼的种群动力学模型，包含和不包含空间分层结构的两种贝叶斯模型被用于分析其种群动力学的大尺度空间异质性。本文分析了不同的假设，来研究小黄鱼种群动力学潜在的变化趋势。研究结果表明小黄鱼种群动力学特征具有明显的时间和空间变化。种群的增长速度从20世纪八十年代开始增加，而可捕系数从1981年到2015年增加了两倍多。与黄渤海亚种群相比，东海的小黄鱼亚种群生长速度更快，遭受的捕捞压力也更大。基于最大可持续产量MSY的参考点表明，无论是整个小黄鱼种群还是两个亚种群，近年来都有非常高的过度捕捞风险。因此我国小黄鱼的渔业管理急需更加保守的管理策略，同时考虑其地域差异。本文所用的方法可以应用于其他种类的资源评估和渔业管理，尤其是具有空间异质性和数据有限的种类。