Strategic transformation of regionalization for the agricultural comprehensive development: The example of Ningxia Hui Autonomous Region in China

Strategic transformation of regionalization for agricultural comprehensive development (ACD) was presented by the Ministry of Finance of the People’s Republic of China (MOF) in 2014. The regionalization is the premise and basis of the sustainable development and improved competitiveness for agriculture. Based on the environmental resources related to agriculture, such as cropland, climate, water resources, terrain, geomorphology, patterns of the ACD projects, distribution of ecological planning, etc., we devised 13 indices using the geographic comprehensive regionalization method. The indices took into account a combination of dynamic and static, qualitative and quantitative, as well as agricultural and ecological factors. The strategic transformation of regionalization for the ACD in Ningxia Hui Autonomous Region of China was performed; seven types were included: prioritized regions, prioritized and restricted regions, protected regions, protected and restricted regions, restricted and prioritized regions, restricted and protected regions, and restricted regions. A further 24 subtypes were used based on locations and ecological zones. The regionalization results showed that prioritized regions were mainly in northern Ningxia, the most suitable area for agriculture. The protected and restricted regions were in central and southern Ningxia. In the central part, drought was the limiting factor for agriculture, and water conservation projects there should be supported. The ecological environment is fragile in southern Ningxia, so there is a need for ecologically sound agriculture to be developed in this region. Such regionalization could achieve two goals, namely agricultural conservation and eco-environmental protection. It was performed following the requirement for scientific regionalization to include three types of regions (prioritized regions, protected regions, and restricted regions), and was applied at the township scale in a provincial or autonomous region for the first time. The results provide both guidance for the strategic transformation of the ACD in Ningxia, and a reference for similar work in other provinces.     

土壤质量评价国外研究进展

土壤是人类赖以生存的根本资源。土壤质量涉及到动植物生产力,大气、水的质量和人类的健康,随着人们对自然资源和环境保护意识的增强,越来越多的国家和地区已将土壤质量评价工作作为实现可持续发展的一个重要方面。通过土壤质量评价,了解土壤管理和利用的现状,为土壤质量的改善及可持续利用提供理论依据和技术支撑。根据国外近10年的研究,总结了主要的评价指标体系和评价方法。评价指标主要包括土壤物理、化学和生物性质3个方面的指标。评价方法分为定性和定量评价,定量评价应用较广,包括土壤质量指数、土壤质量模型、多元线性回归、相对土壤质量法等。掌握和了解国外相关研究的动态,对于开展土地质量地球化学评估及土地的分等定级工作有着重要的意义。     

Climatic variations of general atmospheric circulation, precipitation and river flow of the territory of Kazakhstan

Methods of calculating the basic hydrological characteristics of a water resource assessment, as well as the planning and management of their long-term use are based upon the concept of stationarity of long-term flow fluctuations. However, data of researches by hydrologists and climatologists clearly indicate that there are long-period changes in the characteristics of precipitation and river flow. This article discusses the variations of annual precipitation and river flow in the Ishim River Basin in Kazakhstan, based on the W, C and E classification developed by G.Y. Vangengeim who analyzed the long-term variability of anomalies by the number of days with some form of atmospheric circulation. From this study, the largest anomaly of the macro-circulation processes was revealed, and a comparative analysis of the number of days with various forms of atmospheric circulation and precipitation anomalies was made. It was demonstrated that the nature of atmospheric circulation depends on the distribution of precipitation; however, precipitation is also highly dependent on local physiographic conditions. The analysis of anomalous precipitation during the maximum number of days of positive anomalies with various forms of atmospheric circulation was also carried out. This study presents some results from the preliminary analysis of annual river flow linked with forms of atmospheric circulation.     

Geomorphic response to an active transpressive regime: a case study along the Chaman strike‐slip fault,western Pakistan

The Chaman left‐lateral strike‐slip fault bounds the rigid Indian plate boundary at the western end of the Himalayan‐Tibetan orogen and is marked by contrasting topographic relief. Deformed landforms along the fault provide an excellent record for understanding this actively evolving intra‐continental strike‐slip fault. The geomorphic response of an active transpessional stretch of the Chaman fault was studied using digital elevation model (DEM) data integrated with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Visible and Near Infrared/Short Wave Infrared (VNIR/SWIR) and images from GeoEye‐1. Geologic and geomorphic mapping helped in reconstructing the Late Quaternary landscape history of this transpessional strand of the Chaman strike‐slip fault and the associated Spinatizha thrust fault in western Pakistan. Topographic analysis of a part of the transpression (the thrust bounded Roghani ridge) revealed northward growth of the Spinatizha fault with the presence of three water gaps and two corresponding wind gaps. Geomorphic indices including stream length‐gradient index, mountain front sinuosity, valley floor width to valley height ratios, and entrenchment of recent alluvial fan deposits were used to define the lateral growth and direction of propagation of the Spinatizha fault. Left‐lateral displacement along Chaman fault and uplift along the Spinatizha fault was defined using topographic analysis of the Roghani ridge and geomorphic mapping of an impressive alluvial fan, the Bostankaul fan. The landforms and structures record slip partitioning along the Indian plate boundary, and account for the convergence resulting from the difference in the Chaman fault azimuth and orientation of the velocity vector of the Indian plate. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of a rainfall-runoff model to three catchments in Iraq

Abstract

The capability of the Surface inFiltration Baseflow (SFB) conceptual rainfall-runoff model to simulate streamflow for three catchments selected from northern Iraq is investigated. These catchments differ in their climatic regimes and physical characteristics. Three versions of the model were tested: the original three-parameter model (SFB), the modified five-parameter model (SFB-5), and the modified six-parameter model (SFB-6). The available daily precipitation, potential evapotranspiration and runoff data were used in conjunction with a simulated annealing (SA) optimization technique to calibrate the various versions of the SFB model. A simple sensitivity analysis was then carried out to determine the relative importance of the model parameters. The study indicated that use of the original three parameter model was not adequate to simulate monthly streamflow in the selected catchments. The modified version (SFB-5) provided better runoff simulation than the original SFB model; overall a 19% increase was observed in the coefficient of determination (R²) between simulated and observed monthly runoff. The SFB-5 model performed with varying degrees of success among the catchments. The model performance in the validation stage was reasonable and comparable to that of the calibration stage. The sensitivity analysis of the SFB model for arid catchments revealed that the baseflow parameter (B) was the most sensitive one, while the S and F parameters were less sensitive than the B parameter.     

A SIMPLE SOIL MOISTURE INDEX TO FORECAST CROP YIELDS

Neutron probe soil moisture measurements obtained biweekly during the growing season between 1982 and 1991 from multiple depths under grass-covered plots at 17 Illinois Climate Network sites are used to forecast crop yields. A Soil Moisture Index (SMIX) that combines the effect of intensity, duration, and timing of drought or excessively wet conditions was computed by integrating the quantity of available soil moisture throughout the rooting zone over the growing season. Relationships between the SMIX values and crop yields are evaluated at county, regional, and statewide scales. Coefficients of determination (r ²) for relationships between the SMIX values and maize, soybeans, and hay yields at the statewide level are 0.88, 0.74, and 0.81, respectively, when the period of integration is terminated at the end of the growing season. This new soil index can be employed to forecast yields as early as 12 weeks before harvest for the state of Illinois. However, predictions with RMSE ≤ 10% of the mean yield can be achieved only for SMIX integration periods ending 5, 9, and 6 weeks before harvest for maize, soybeans, and hay, respectively. Nomograms are presented for using the relationships between the SMIX values and crop yields to forecast Illinois's major crops well before harvest.     

Evaluation of fuzzy-based classifiers for cotton crop identification

In this study, an evaluation of fuzzy-based classifiers for specific crop identification using multi-spectral temporal data spanning over one growing season has been carried out. The temporal data sets have been georeferenced with 0.3 pixel rms error. Temporal information of cotton crop has been incorporated through the following five indices: simple ratio (SR), normalized difference vegetation index (NDVI), transformed normalized difference vegetation index (TNDVI), soil-adjusted vegetation index (SAVI) and triangular vegetation index (TVI), to study the effect of indices on classified output. For this purpose, a comparative study between two fuzzy-based soft classification approaches, possibilistic c-means (PCM) and noise classifier (NC), was undertaken. In this study, advanced wide field sensor (AWiFS) data for soft classification and linear imaging self scanner sensor (LISS III) data for soft testing purpose from Resourcesat-1 (IRS-P6) satellite were used. It has been observed that NC fuzzy classifier using TNDVI temporal index – dataset 2, which comprises four temporal images performs better than PCM classifier giving highest fuzzy overall accuracy of 96.03%.     

Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks

Understanding rock material characterizations and solving relevant problems are quite difficult tasks because of their complex behavior, which sometimes cannot be identified without intelligent, numerical, and analytical approaches. Because of that, some prediction techniques, like artificial neural networks (ANN) and nonlinear regression techniques, can be utilized to solve those problems. The purpose of this study is to examine the effects of the cycling integer of slake durability index test on intact rock behavior and estimate some rock properties, such as uniaxial compressive strength (UCS) and modulus of elasticity (E) from known rock index parameters using ANN and various regression techniques. Further, new performance index (PI) and degree of consistency (Cd) are introduced to examine the accuracy of generated models. For these purposes, intact rock dataset is established by performing rock tests including uniaxial compressive strength, modulus of elasticity, Schmidt hammer, effective porosity, dry unit weight, p‐wave velocity, and slake durability index tests on selected carbonate rocks. Afterward, the models are developed using ANN and nonlinear regression techniques. The concluding remark given is that four‐cycle slake durability index (I_d4) provides more accurate results to evaluate material characterization of carbonate rocks, and it is one of the reliable input variables to estimate UCS and E of carbonate rocks; introduced performance indices, both PI and Cd, may be accepted as good indicators to assess the accuracy of the complex models, and further, the ANN models have more prediction capability than the regression techniques to estimate relevant rock properties. Copyright © 2011 John Wiley & Sons, Ltd.     

基于遥感影像的大郑东新区景观格局现状分析

研究基于RS和GIS技术,以研究区的土地利用现状图和2009年3月5号SPOT 5卫星的10 m多光谱遥感影像数据为主要数据源,结合研究区近年来的社会经济资料和实地调查记录,在深入分析研究区景观生态格局时空演变特征的基础上,以ENVI4. 5和Fragstats 3. 3软件作为支持工具,从具体的景观生态空间,提取能够...     

Ecological quality assessment of small estuaries from the Portuguese coast based on fish assemblages indices

The importance of establishing the ecological quality of estuarine systems has been widely acknowledged and led to the development of several fish community-based multimetric indices. Nevertheless, a question rose about the accuracy of these tools when natural disturbance is acting upon the organization of the systems’ communities. Four multimetric indices were used to examine their ability to differentiate the ecological status of five small estuarine systems (southern Portugal), and also to test if they reflected the level of anthropogenic pressures. Fish assemblages from Mira, Odeceixe and Aljezur (in the Southwest coast), Gilão and Bensafrim (in the South coast) estuaries were sampled seasonally for one year, and anthropogenic sources of pressure were identified and quantified. We found that although the applied indices provided information on ecological condition differentiation among systems, they are unable to explain different classes of ecological status in systems with equivalent pressure levels.