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.     

The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide-susceptibility map of its near vicinity

Landslides are common natural hazards in the seismically active North Anatolian Fault Zone of Turkey. Although seismic activity, heavy rainfall, channel incisions, and anthropogenic effects are commonly the main triggers of landslides, on March 17, 2005, a catastrophic large landslide in Sivas, northeastern of Turkey, the Kuzulu landslide, was triggered by snowmelt without any other precursor. The initial failure of the Kuzulu landslide was rotational. Following the rotational failure, the earth material in the zone of accumulation exhibited an extremely rapid flow caused by steep gradient and high water content. The Agnus Creek valley, where Kuzulu village is located, was filled by the earth-flow material and a landslide dam was formed on the upper part of Agnus Creek. The distance from the toe of the rotational failure down to the toe of the earth flow measured more than 1800 m, with about 12.5 million m³ of displaced earth material. The velocity of the Kuzulu landslide was extremely fast, approximately 6 m/s. The main purposes of this study are to describe the mechanism and the factors conditioning the Kuzulu landslide, to present its environmental impacts, and to produce landslide-susceptibility maps of the Kuzulu landslide area and its near vicinity. For this purpose, a detailed landslide inventory map was prepared and geology, slope, aspect, elevation, topographic-wetness index and stream-power index were considered as conditioning factors. During the susceptibility analyses, the conditional probability approach was used and a landslide-susceptibility map was produced. The landslide-susceptibility map will help decision makers in site selection and the site-planning process. The map may also be accepted as a basis for landslide risk-management studies to be applied in the study area.     

Critical rainfall statistics for predicting watershed flood responses: rethinking the design storm concept

Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.     

Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions

The most popular practice for analysing nonstationarity of flood series is to use a fixed single‐type probability distribution incorporated with the time‐varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time‐varying under changing environments. To allow the investigation of this complex nature, the time‐varying two‐component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series of two stations in the Weihe River basin, with the model parameters calibrated by the meta‐heuristic maximum likelihood method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single‐type distributions, stationary mixture distributions and time‐varying single‐type distributions. The results highlighted the advantages of TTMD with physically‐based covariates for both stations. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. Copyright © 2016 John Wiley & Sons, Ltd.     

Recultivation of abandoned agricultural lands in Ukraine: Patterns and drivers

The recent rise in agricultural commodity prices and the expectation that high price will persist have triggered a wave of farmland expansion in regions where land resources are still available. One such region is the former Soviet Union, where the collapse of socialism caused massive agricultural abandonment and where some of these lands are now being brought back into production. Yet, the extent and spatial patterns of recultivation, and what determines these patterns, remains unclear. We examined the extent of recultivation of abandoned agricultural land in Ukraine since 2007 using a new, satellite-based recultivation map and assessed the effect of biophysical and socioeconomic determinants on recultivation patterns using boosted regression trees. We found key predictors of recultivation to be related to the suitability of land for agriculture (i.e., soil quality, temperature). Accessibility to major cities was also important, with most recultivation happening closer to settlements, but this influence varied across Ukraine. Variables related to agricultural management (fertilizer input, mechanization) and demography were negligible in explaining recultivation in our analyses. These factors suggest that recultivation patterns were primarily driven by factors related to land productivity, with recultivation focusing on the most promising areas. Given the remaining large amount of unused agricultural land in Eastern Europe and the former Soviet Union, and considering that much abandonment occurred in areas only marginally suited to agriculture, our findings provide important insights into where recultivation can be expected to happen and thus for assessing the potential socioeconomic and environmental impacts of recultivation.     

年最大值抽样估算的暴雨频率设计值的低估问题探讨

由年最大值抽样（AMS）和年超大值抽样（AES）的基本理论及重现期（RP）的定义可知,AMS并不符合以“事件”为基础的重现期的定义.以美国西南半干旱区1438个雨量站和太湖流域96个雨量站的降雨资料为例,通过经验频率与超过概率的比较,发现AMS估算的暴雨频率设计值偏小,尤其是对常遇频率降雨设计值的影响更加显著.美国的降雨量资料站点多、系列长,实际资料验证与理论分析一致.通过对太湖流域AMS资料的分布形态进行分析的结果表明：太湖流域的站点不多,资料长度不够,且大部分站点在雨量大值区数据稀少,使得频率直方图不连续,是造成我国太湖流域的资料验证效果不理想的可能原因.     

部分变量误差模型的整体抗差最小二乘估计

部分变量误差模型(partial EIV model)的加权整体最小二乘(weighted total least-squares,WTLS)估计不具备抵御粗差的能力。鉴于粗差可能同时出现在观测值和系数矩阵中,本文在提出部分变量误差模型WTLS估计的两步迭代解法的基础上,运用抗差M估计的等价权方法,发展了一种整体抗差最小二乘(TRLS)估计方法,并采用一致最大功效统计量确定降权因子。针对WTLS估计两步迭代解法的特点,设计了两个不同的降权方案:第1个方案是在估计系数矩阵元素时,不对观测值降权,仅对系数矩阵降权;第2个方案是在估计系数矩阵元素时,既对系数矩阵降权,同时也对观测值降权。通过对模拟2D仿射变换和线性拟合实例进行计算和分析,结果表明第1方案优于第2方案,并且优于基于残差和验后单位权方差的抗差估计和现有的变量误差模型抗差估计。     

干涉图像第二类统计Goldstein自适应滤波方法

干涉图滤波是InSAR数据处理中的关键步骤之一,滤波结果的优劣会直接影响到相位观测的质量和最终产品精度。本文结合干涉图滤波算法的研究进展,对Goldstein频率域滤波及其经典改进算法进行了系统分析和比较,在此基础上提出了一种基于第二类统计的稳健相干性估计量的Goldstein自适应滤波方法。本文采用模拟数据和Envisat ASAR真实数据与现有方法进行了验证,试验结果表明,新的滤波方法在保持细节和抑制噪声方面优势更加明显。     

地理国情普查试点成果综合分析

城镇服务设施布局的评价与分析是地理国情普查综合统计分析城镇化发展的重要内容。针对当前城镇化发展不平衡,生活服务设施空间布局不合理的情况,该文利用克拉玛依市独山子区地理国情普查试点成果,结合专题数据,采用GIS网络分析方法,在独山子区城镇综合设施之间配置最短最优路径。耦合结果表明:老城区卫生资源分布较合理,但是教育资源和整体服务设施分布却过于集中。这种方法还可以进一步用于优化城镇功能单元布局与服务保障设施点的建设,完善居民出行、教育、日常生活和文化服务等方面。