Pashmina production and socio‐economic changes in the Indian Changthang: Implications for natural resource management

A unique pastoral community uses the arid rangelands of eastern Ladakh, known as Changthang, northern India. The nomadic people rear a variety of livestock such as sheep, goats, horses and yaks, which provide them with various goods and services. Nevertheless, the needs and aspirations of the people are changing. There is a trend towards increasing the livestock population, especially of a breed of goat that produces one of the finest natural fibres: Pashmina, which is the mainstay of their economy. This increase in goat population, however, is jeopardising the long‐term survival of the wild herbivores in the region, and as such is not sustainable. We present information on the current trends in socio‐economy, Pashmina production, wildlife conservation, and the conflicts of interest between wildlife and nomads in the region. On the basis of this information, we make suggestions for the conservation of natural resources in the region. We recommend preserving the historical societal norms and notions of the people, and capitalising on them to manage natural resources. We also recommend joint management of natural resources by the local people, State and non‐governmental organisations. Our findings provide a platform on which a grazing policy for the region may be formulated.     

Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM1

Harshburger, Brian J., Karen S. Humes, Von P. Walden, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2010. Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM. Journal of the American Water Resources Association (JAWRA) 46(3):603-617. DOI: 10.1111/j.1752-1688.2010.00437.x Abstract: As demand for water continues to escalate in the western United States, so does the need for accurate streamflow forecasts. Here, we describe a methodology for generating short-to-medium range (1 to 15 days) streamflow forecasts using an enhanced version of the Snowmelt Runoff Model (SRM), snow-covered area data derived from MODIS products, data from Snow Telemetry stations, and meteorological forecasts. The methodology was tested on three mid-elevation, snowmelt-dominated basins ranging in size from 1,600 to 3,500 km². To optimize the model performance and aid in its operational implementation, two enhancements have been made to SRM: (1) the use of an antecedent temperature index method to track snowpack cold content, and (2) the use of both maximum and minimum critical temperatures to partition precipitation into rain, snow, or a mixture of rain and snow. The comparison of retrospective model simulations with observed streamflow shows that the enhancements significantly improve the model performance. Streamflow forecasts generated using the enhanced version of the model compare well with the observed streamflow for the earlier leadtimes; forecast performance diminishes with leadtime due to errors in the meteorological forecasts. The three basins modeled in this research are typical of many mid-elevation basins throughout the American West, thus there is potential for this methodology to be applied successfully to other mountainous basins.     

Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds1

Maurer, Edwin P., Levi D. Brekke, and Tom Pruitt, 2010. Contrasting Lumped and Distributed Hydrology Models for Estimating Climate Change Impacts on California Watersheds. Journal of the American Water Resources Association (JAWRA) 46(5):1024–1035. DOI: 10.1111/j.1752-1688.2010.00473.x Abstract: We compare the projected changes to streamflows for three Sierra Nevada rivers using statistically downscaled output from 22 global climate projections. The downscaled meteorological data are used to drive two hydrology models: the Sacramento Soil Moisture Accounting model and the variable infiltration capacity model. These two models differ in their spatial resolution, computational time step, and degree and objective of calibration, thus producing significantly different simulations of current and future streamflow. However, the projected percentage changes in monthly streamflows through mid-21st Century generally did not differ, with the exceptions of streamflow during low flow months, and extreme low flows. These findings suggest that for physically based hydrology models applied to snow-dominated basins in Mediterranean climate regimes like the Sierra Nevada, California, model formulation, resolution, and calibration are secondary factors for estimating projected changes in extreme flows (seasonal or daily). For low flows, hydrology model selection and calibration can be significant factors in assessing impacts of projected climate change.     

Sensitivity of Stream flow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed1

Dai, Zhaohua, Carl C. Trettin, Changsheng Li, Devendra M. Amatya, Ge Sun, and Harbin Li, 2010. Sensitivity of Streamflow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed. Journal of the American Water Resources Association (JAWRA) 1–13. DOI: 10.1111/j.1752-1688.2010.00474.x Abstract: A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for predicting the streamflow and water table dynamics for this watershed with an acceptable model efficiency (E > 0.5 for daily streamflow and >0.75 for monthly streamflow). The simulation results from changing temperature and precipitation scenarios indicate that climate change influences both streamflow and water table in the forested watershed. Compared to current climate conditions, the annual average streamflow increased or decreased by 2.4% with one percentage increase or decrease in precipitation; a quadratic polynomial relationship between changes in water table depth (cm) and precipitation (%) was found. The annual average water table depth and annual average streamflow linearly decreased with an increase in temperature within the range of temperature change scenarios (0-6°C). The simulation results from the potential climate change scenarios indicate that future climate change will substantially impact the hydrological regime of upland and wetland forests on the coastal plain with corresponding implications to altered ecosystem functions that are dependent on water.     

Hydrologic Modeling of an Extreme Flood in the Guadalupe River in Texas1

Sharif, Hatim O., Almoutaz A. Hassan, Sazzad Bin-Shafique, Hongjie Xie, and Jon Zeitler, 2010. Hydrologic Modeling of an Extreme Flood in the Guadalupe River in Texas. Journal of the American Water Resources Association (JAWRA) 1-11. DOI: 10.1111/j.1752-1688.2010.00459.x Abstract: Many of the storms creating the greatest rainfall depths in Texas, measured over durations ranging from one minute to 48 hours, have occurred in the Texas Hill Country area. The upstream portion of the Guadalupe River Basin, located in the Texas Hill Country, is susceptible to flooding and rapid runoff due to thin soils, exposed bedrock, and sparse vegetation, in addition to the Balcones Escarpment uplift contributing to precipitation enhancement. In November 2004, a moist air mass from the Gulf of Mexico combined with moist air from the Pacific Ocean resulted in the wettest November in Texas since 1895. Although the peak discharges were not the highest on record, the U.S. Geological Survey (USGS) stream gauge on the Guadalupe River at Gonzales, Texas reported a daily mean discharge of 2,304 m³/s on November 23, 2004 (average discharge is 53 m³/s). In this paper, we examine the meteorological conditions that led to this event and apply a two-dimensional, physically based, distributed-parameter hydrologic model to simulate the response of a portion of the basin during this event. The study results clearly demonstrate the ability of physically based, distributed-parameter simulations, driven by operational radar rainfall products, to adequately model the cumulative effect of two rainfall events and route inflows from three upstream watersheds without the need for significant calibration.     

Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

Abstract: The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km² mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature‐index, (2) the temperature‐index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature‐based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE‐UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975‐1985 and 1986‐1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975‐1985 and validated using monthly runoff from 1986‐1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature‐index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature‐index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature‐index plus elevation band models could provide almost equally good runoff simulation results.     

Modeling the Potential of the Northern China Forest Shelterbelt in Improving Hydroclimate Conditions1

Abstract: The forest shelterbelt (afforestation) project in northern China is the most significant ecosystem project initiated in China during the past three decades. It aims to improve and conserve the ecological environment in the project areas. The tree belt stands along the southern edge of the sandy lands, nearly paralleling to the Great Wall. This study used a regional climate model to simulate the potential of improving regional hydroclimate conditions resulting from the afforestation project. Two simulations with preafforestation and postafforestation land cover were performed over East Asia from January 1987 to February 1988. The model resolution is 60 km. The differences between the two simulations suggest that the northern China forest shelterbelt project is likely to improve overall hydroclimate conditions by increasing precipitation, relative humidity, and soil moisture, and by reducing prevailing winds and air temperature. The effects are more significant in spring and summer than fall and winter. Changes in many hydrologic properties (e.g., evapotranspiration, soil moisture, and water yield), however, differ between the dry Northeast China and the moist Northeast China. The hydroclimate effects are also found in the surrounding areas, featured by noticeably moister conditions in the area south of the afforestation project. The results imply that the shelterbelt project would reduce water yield in afforested Northwest and North China during spring, but increase water yield in the afforested Northeast China as well as in the southern surrounding area, offset some greenhouse effects, and reduce the severity of dust storms. Possible improvements of this study by using actual afforestation data, modeling with higher resolution, longer integration and more detailed processes, and analyzing the physical mechanisms are discussed.     

昆明市松华坝水源保护区水资源安全综合评价

通过对昆明市松华坝水源保护区自然生态、水资源、经济社会情况的调查与分析,建立了保护区水资源安全评价指标体系,并分别采用层次分析法、模糊评判法和集对分析法对保护区水资源安全进行综合评价。结果表明,目前评价区的水资源安全处于基本安全级别。     

荒漠河岸多枝柽柳灌丛碳氮磷化学计量特征及其影响因素

为了解群落水平下荒漠河岸多枝柽柳（Tamarix ramosissima Ledeb.）灌丛的碳氮磷化学计量特征及其影响因素,在黑河下游荒漠河岸3 800 m范围内,沿垂直河道方向上设置9个采样点,采用相关性分析、冗余分析（RDA）和偏冗余分析（pRDA）方法,对多枝柽柳群落的碳氮磷化学计量格局及其与环境因子的关系进行研究.结果表明:黑河下游荒漠河岸多枝柽柳群落TC、TN、TP含量平均值分别为380.27、30.42和1.54 mg/g,C:N、C:P和N:P平均值分别为12.98、257.09和20.04.与全球和区域尺度物种水平研究相比,黑河下游荒漠河岸多枝柽柳灌丛群落具有较低的TC含量、较高的TN含量和N:P以及相对稳定的TP含量.多枝柽柳灌丛群落碳氮磷化学计量特征变异系数相对较小,内稳性较强,相对较高的N:P（14.55~27.20）表明群落水平下多枝柽柳灌丛更倾向于受磷元素的限制.在沿河梯度上,多枝柽柳群落TC含量和TN含量均随沿河距离的增加呈显著下降的变化趋势,而C:N随沿河距离的增加呈波动上升的变化趋势;TP含量呈先降后升的变化趋势,而C:P和N:P大致呈先上升后下降的变化趋势.多枝柽柳灌丛群落的碳氮磷化学计量特征与土壤理化属性存在一定相关性,土壤含水量、土壤容重和土壤pH是影响多枝柽柳群落碳氮磷化学计量特征变化的关键因子,三者共同解释了总变异的57.7%,其中土壤含水量解释了总变异的32.8%.研究显示,土壤水盐与多枝柽柳灌丛的碳氮磷化学计量特征关系密切,土壤含水量在解释多枝柽柳灌丛碳氮磷化学计量特征变化方面比土壤pH更为重要.      

三峡小江回水区蓝藻季节变化及其与主要环境因素的相互关系

三峡水库支流回水区富营养化和水华近年来备受关注.通过对库区小江流域回水区段蓝藻群落组成及丰度的监测研究发现,2007年5月~2008年5月小江回水区共鉴定出蓝藻15属,40种,其细胞密度均值为(23.50±10.30)×105cells.L-1,占藻类总密度的24.1%,生物量均值为(768.70±287.40)μg.L-1,占藻类总生物量的8.9%.蓝藻丰度季节变化明显,春末夏初为蓝藻的繁盛期,盛夏后蓝藻丰度逐渐下降,并在冬季达到全年最低水平.鱼腥藻、平裂藻、束丝藻、席藻、微囊藻是常见蓝藻,它们的细胞密度总和约占蓝藻细胞总密度的79.1%,生物量总和约占蓝藻总生物量的77.6%,是小江回水区蓝藻的优势种群.对蓝藻丰度和营养物、温度、透明度、真光层深度等环境因素的相关性分析发现,小江回水区蓝藻生长对无机态氮、磷的吸收利用显著,且蓝藻生长摄取硝态氮可能比利用氨氮更加明显.温度升高、水下光学透射性能下降有利于蓝藻细胞密度和生物量的增加.结合研究同期水文、气象条件的观测结果,发现在降雨、径流的作用下,水土流失严重的小江回水区氮、磷营养物同泥沙一起输入水体,为蓝藻生长提供丰厚的物质基础.受泥沙颗粒的影响,水体混浊度提高而真光层深度减少,蓝藻自身对低光照、高浊条件的敏感性及其悬浮生长机制促其能够在上层水体大量生长并形成优势.