利用TM图像进行干旱荒漠带牧区土地资源调查

选用TM卫片作为调查基础资料,结合地形图和局部地区大比例尺航片,完成了甘肃河西地域三个牧业县的土地利用现状调查,为遥感技术在干旱荒漠地带牧区进行土地资源调查找出了效果好、经济的方法。     

Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data

While existing remote sensing-based drought indices have characterized drought conditions in arid regions successfully, their use in humid regions is limited. We propose a new remote sensing-based drought index, the Scaled Drought Condition Index (SDCI), for agricultural drought monitoring in both arid and humid regions using multi-sensor data. This index combines the land surface temperature (LST) data and the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and precipitation data from Tropical Rainfall Measuring Mission (TRMM) satellite. Each variable was scaled from 0 to 1 to discriminate the effect of drought from normal conditions, and then combined with the selected weights. When tested against in-situ Palmer Drought Severity Index (PDSI), Palmer's Z-Index (Z-Index), 3-month Standardized Precipitation Index (SPI), and 6-month SPI data during a ten-year (2000-2009) period, SDCI performed better than existing indices such as NDVI and Vegetation Health Index (VHI) in the arid region of Arizona and New Mexico as well as in the humid region of North Carolina and South Carolina. The year-to-year changes and spatial distributions of SDCI over both arid and humid regions generally agreed to the changes documented by the United States Drought Monitor (USDM) maps.     

基于SAR数据的干旱区冲积扇地表粗糙度反演

干旱区冲积扇的表面特征是研究古气候、古环境变化的重要途径,冲积扇扇面粗糙度是反映冲积扇演化的重要指示。合成孔径雷达(SAR)已成为冲积扇扇面特征参数提取的有力工具。然而,现有的地表粗糙度反演模型在干旱区难以得到较好的反演结果。利用Radarsat-2极化数据,开展了疏勒河冲积扇地表粗糙度反演研究,在OH模型的基础上,提出了更加适合干旱区地表粗糙度反演的新方法。经过实测数据的验证,新方法能够解决原有模型在干旱区粗糙度反演结果偏大的问题,并取得了较好的反演结果。该模型的提出为干旱区冲积扇表面参数提取提供了可靠的工具。     

林地调查中的面积单元线性测量法（SL法）

林业调查中采用的基本方法是全林调查法和局部估测法,而局部估测方法中最常用的是角规测量法与标准地法,在林地调查中角规法误差较大,而标准地法又存在着难于布设的问题。本研究提出的面积单元线性测量法,可方便快捷地进行局部估测,节省人力和时间,同时又达到了较高的精度,特别适用于不规则林分的调查。     

Multilevel Approach for Optimizing Land and Water Resources and Irrigation Deliveries for Tertiary Units in Large Irrigation Schemes. I: Method

This paper presents the area and water allocation model (AWAM), which incorporates deficit irrigation for optimizing the use of water for irrigation. This model was developed for surface irrigation schemes in semiarid regions under rotational water supply. It allocates the land area and water optimally to the different crops grown in different types of soils up to the tertiary level or allocation unit. The model has four phases. In the first phase, all the possible irrigation strategies are generated for each crop-soil-region combination. The second phase prepares the irrigation program for each strategy, taking into account the response of the crop to the water deficit. The third phase selects the optimal and efficient irrigation programs. In the fourth phase of the model, irrigation programs are modified by incorporating the conveyance and the distribution efficiencies. These irrigation programs are then used for allocating the land and water resources and preparing the water release schedule for the canal network.     

Climate Change and Future Long-Term Trends of Rainfall at North-East of Iraq

Iraq is facing water shortage problem despite the presence of the Tigris and Euphrates Rivers. In this research, long rainfall trends up to the year 2099 were studied in Sulaimani city northeast Iraq to give an idea about future prospects. The medium high （A2） and medium low B2 scenarios have been used for purpose of this study as they are more likely than others scenarios, that beside the fact that no climate modeling canter has performed GCM （global climate model） simulations for more than a few emissions scenarios （HadCM3 has only these two scenarios） otherwise pattern scaling can be used for generating different scenarios which entail a huge uncertainty. The results indicate that the average annual rainfall shows a significant downward trend for both A2 and B2 scenarios. In addition, winter projects increase/decrease in the daily rainfall statistics of wet days, the spring season show very slight drop and no change for both scenarios. However, both summer and autumn shows a significant reduction in maximum rainfall value especially in 2080s while the other statistics remain nearly the same. The extremes events are to decrease slightly in 2080s with highest decrease associated with A2 scenario. This is due to the fact that rainfall under scenario A2 is more significant than under scenario B2. The return period of a certain rainfall will increase in the future when a present storm of 20 year could occur once every 43 year in the 2080s. An increase in the frequency of extreme rainfall depends on several factors such as the return period, season of the year, the period considered as well as the emission scenario used.     

Grasses for biofuels: A low water-use alternative for cold desert agriculture?

In arid regions, reductions in the amount of available agricultural water are fueling interest in alternative, low water-use crops. Perennial grasses have potential as low water-use biofuel crops. However, little is known about which perennial grasses can produce high quantity, high quality yields with low irrigation on formerly high-input agricultural fields in arid regions. We monitored biomass production, weed resistance, rooting depth, and root architecture of nine perennial grasses under multiple irrigation treatments in western Nevada. Under a low irrigation treatment (71 ± 9 cm irrigation water annually), cool-season grasses produced more biomass and were more weed-resistant than warm-season grasses. With additional irrigation (120 ± 12 cm water annually), warm- and cool-season grasses had similar biomass production, but cool-season species remained more weed-resistant. Among species within each grass type, we observed high variability in performance. Two cool-season species (Elytrigia elongata and Leymus cinereus) and one warm-season species (Bothriochloa ischaemum) performed better than the other tested species. Root depth was not correlated with biomass production, but species with deeper roots had fewer weeds. Abundance of fine roots (but not large roots) was correlated with increased biomass and fewer weeds. Both L. cinereus and E. elongata had deep root systems dominated by fine roots, while B. ischaemum had many fine roots in shallow soil but few roots in deeper soil. Cool-season grasses (particularly E. elongata, L. cinereus, and other species with abundant fine roots) may be worthy of further attention as potential biofuel crops for cold desert agriculture.     

A GIS Database for Sustainable Management of Shallow Water Resources in the Tulul al Ashaqif Region, NE Jordan

The Tulul al Ashaqif region is an arid area in northeastern Jordan that contains renewable shallow perched aquifer water. The study of these aquifers has led to better understanding of the recharge process as well as other hydrological issues related to management of water resources in similar areas. The use of geographic information system (GIS)-based predictive mapping to locate areas of high potential for shallow perched aquifer sites is explored in this paper. Knowledge of the hydrologic, geologic and geomorphic variables influencing the development of shallow aquifer formation is used to produce GIS layers representing the spatial distribution of those variables. The GIS layers are then analyzed to identify locations where combinations of environmental variables match patterns observed at known sites. In addition, information can be deduced on the volume of water that is available and the best locations to site recharge facilities. Moreover, future development of these resources requires consideration of possible adverse affects of usage on these resources. The database developed can be used for this purpose as well.     

The current bioenergy production potential of semi-arid and arid regions in sub-Saharan Africa

This article assesses the current technical and economic potential of three bioenergy production systems (cassava ethanol, jatropha oil and fuelwood) in semi-arid and arid regions of eight sub-Saharan African countries. The results indicate that the availability of land for energy production ranges from 2% (1.3 Mha) of the total semi-arid and arid area in South Africa to 21% (12 Mha) in Botswana. Land availability for bioenergy production is restricted mainly by agricultural land use, but also by steep slopes and biodiversity protection. The current total technical potential for the semi-arid and arid regions of the eight countries is calculated to be approximately 300 PJ y⁻¹ for cassava ethanol production, 600 PJ y⁻¹ for jatropha biodiesel or 4000 PJ y⁻¹ for fuelwood. The analysis of economic potentials shows that in many semi-arid regions, cassava ethanol, jatropha oil and fuelwood can compete economically with the reference energy sources. However, fuelwood, jatropha oil, and cassava ethanol production costs in most arid regions of sub-Saharan Africa are often above average national market prices of gasoline, diesel, and fuelwood. Nevertheless, for example, in arid Kenya 270 PJ could be produced annually with fuelwood at production costs of less than 3 US$ GJ⁻¹. Despite high production costs, it is important to investigate and invest in sustainable bioenergy production in semi-arid and arid regions of sub-Saharan Africa because of its potential to drive rural economic and social development.     

Participatory landscape analysis to guide restoration of ponderosa pine ecosystems in the American Southwest

Over the past 5 decades, stand-replacing crown fires have increased in size and frequency throughout the long-needled pine forests of the American Southwest. Suppression of frequent, low-intensity ground fires has resulted in dense stands of fire-prone trees over large areas. Efforts to restore forest structure to conditions that would permit a return to historical fire regimes, characterized by frequent ground fire, are hindered by the inability of managers and the public to compare the effects of alternative forest management practices on fire behavior and a host of other issues. Currently, forest management is mired in controversy, endangering ecosystem function, biodiversity, public safety, and municipal watersheds. Our research program, motivated by the need to examine cumulative effects of many independent management decisions over large planning areas, focuses on the development of spatial data and modeling tools that enable diverse stakeholders to work together to guide landscape-scale planning efforts. Data layers describing forest composition and structure facilitate modeling of fire threat and wildlife habitat over areas of several hundred thousand hectares. Modeling alternative forest management scenarios via a collaborative, public process fosters informed discourse and helps conflicting parties forge appropriate policy and identify management responses that meet restoration objectives.