Up‐scaling potential impacts on water flows from agricultural water interventions: opportunities and trade‐offs in the Osman Sagar catchment,Musi sub‐basin,India

Agricultural water management (AWM) has been shown to improve and secure yields in the tropics and has been suggested as an important way to combat poverty in the region. In this paper, we describe potential impacts on upstream and downstream flows of extensive AWM interventions, using the watershed development programme of the Osman Sagar catchment of Musi sub‐basin, Andhra Pradesh semi‐arid India, as an example. Various AWM interventions are compared with a non‐intervention state and the current state of the study area, using 31 years of data by application of the calibrated and validated ARCSWAT 2005 (Version 2.1.4a) modelling tool. Different AWM interventions contribute to improved livelihoods of upstream smallholder farmers by increasing soil moisture availability and groundwater recharge, which can subsequently be used for irrigation. The result is higher crop production and hence larger incomes. Moreover, lower flow intensities and sediment losses reduced by 30–50%, reducing the risk of flooding and sediment accumulation in the Osman Sagar drinking water reservoir. On the other hand, AWM interventions are predicted to result in reduced total water inflows to the Osman Sagar reservoir from 11% of the total annual rainfall (754 mm) recorded at present, to 8% if AWM interventions were implemented at large scale throughout the catchment. A cost–benefit analysis of AWM interventions showed that the highest net economic returns were achieved at intermediate intervention levels (only in‐situ AWM). Copyright © 2012 John Wiley & Sons, Ltd.     

Snowpack variability across various spatio‐temporal resolutions

High‐resolution snow depth (SD) maps (1 × 1 m) obtained from terrestrial laser scanner measurements in a small catchment (0.55 km²) in the Pyrenees were used to assess small‐scale variability of the snowpack at the catchment and sub‐grid scales. The coefficients of variation are compared for various plot resolutions (5 × 5, 25 × 25, 49 × 49, and 99 × 99 m) and eight different days in two snow seasons (2011–2012 and 2012–2013). We also studied the relation between snow variability at the small scale and SD, topographic variables, small‐scale variability in topographic variables. The results showed that there was marked variability in SD, and it increased with increasing scales. Days of seasonal maximum snow accumulation showed the least small‐scale variability, but this increased sharply with the onset of melting. The coefficient of variation (CV) in snowpack depth showed statistically significant consistency amongst the various spatial resolutions studied, although it declined progressively with increasing difference between the grid sizes being compared. SD best explained the spatial distribution of sub‐grid variability. Topographic variables including slope, wind sheltering, sub‐grid variability in elevation, and potential incoming solar radiation were also significantly correlated with the CV of the snowpack, with the greatest correlation occurring at the 99 × 99 m resolution. At this resolution, stepwise multiple regression models explained more than 70% of the variance, whereas at the 25 × 25 m resolution they explained slightly more than 50%. The results highlight the importance of considering small‐scale variability of the SD for comprehensively representing the distribution of snowpack from available punctual information, and the potential for using SD and other predictors to design optimized surveys for acquiring distributed SD data. Copyright © 2014 John Wiley & Sons, Ltd.     

Flow behaviour,suspended sediment transport and transmission losses in a small (sub‐bank‐full) flow event in an Australian desert stream

The behaviour of a discrete sub‐bank‐full flow event in a small desert stream in western NSW, Australia, is analysed from direct observation and sediment sampling during the flow event and from later channel surveys. The flow event, the result of an isolated afternoon thunderstorm, had a peak discharge of 9 m³/s at an upstream station. Transmission loss totally consumed the flow over the following 7·6 km. Suspended sediment concentration was highest at the flow front (not the discharge peak) and declined linearly with the log of time since passage of the flow front, regardless of discharge variation. The transmission loss responsible for the waning and eventual cessation of flow occurred at a mean rate of 13.2% per km. This is quite rapid, and is more than twice the corresponding figure for bank‐full flows estimated by Dunkerley (1992) on the same stream system. It is proposed that transmission losses in ephemeral streams of the kind studied may be minimized in flows near bank‐full stage, and be higher in both sub‐bank‐full and overbank flows. Factors contributing to enhanced flow loss in the sub‐bank‐full flow studied included abstractions of flow to pools, scour holes and other low points along the channel, and overflow abstractions into channel filaments that did not rejoin the main flow. On the other hand, losses were curtailed by the shallow depth of banks wetted and by extensive mud drapes that were set down over sand bars and other porous channel materials during the flow. Thus, in contrast with the relatively regular pattern of transmission loss inferred from large floods, losses from low flows exhibit marked spatial variability and depend to a considerable extent on streamwise variations in channel geometry, in addition to the depth and porosity of channel perimeter sediments. Copyright © 1999 John Wiley & Sons, Ltd.     

华南花岗质潜火山杂岩与富铀矿的成矿关系及找矿前景

本文探讨了华南地区火山岩型或花岗岩型富铀矿，与岩浆旋回晚期的构造－岩浆活动的关系，火山岩型富铀矿离不开大规模火山活动的晚期次火山活动，而花岗岩型富铀矿，则与主侵入晚期的中细粒，不等粒小岩体密切相关，经过长期研究，根据岩浆作用性质，将这套独具特色并与富铀矿的形成息息相关的岩定，定为花岗质潜火山杂岩。     

上海及周边主要城镇城市用地扩展空间特征及其比较

基于多时段TM遥感影像资料,运用缓冲分析法对上海市区及其周边主要城镇城市用地扩展的时空特征进行了分析和比较。研究结果表明:1)区域城市土地利用扩展过程主要受距中心市区(CBD)的距离的影响;2)城市用地扩展在距CBD10km范围内主要表现为上海市区扩展的空间异向性,距CBD10km范围之外城市扩展的异向性则源于不同时期、不同方向上周边城镇的异速扩展过程,并受河流、渠系等小尺度地貌格局差异的影响;3)上海主要郊区城镇扩展可分为标准型、被动扩展型、平缓扩展型和不规则扩展型。