WATER QUALITY FROM TWO SMALL FORESTED WATERSHEDS IN SOUTHERN ILLINOIS1

Two intermittent streams on oak-hickory watersheds in southern Illinois were gaged with a V-notched weir and sampled with an automatic water sampler. For three years data were collected on flow volume and water quality. Flow volumes show large variations between years and watersheds. Samples were analyzed for Na⁺, K⁺, Ca⁺⁺, Mg⁺⁺, P, and NO^-₃. Water quality was consistently high, although there were significant differences between watersheds. A baseline for water quality has been established for comparison after one of the watersheds is clearcut at a later date.     

ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION1

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R²= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R² value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.     

HYDROLOGIC EFFECTS OF THE TONKAWA CREEK FLOOD ABATEMENT PROGRAM1

ABSTRACT: Floodwater-retarding impoundments, controlling 68 percent of the drainage area of Tonkawa Creek, a Washita River tributary in southwestern Oklahoma, have reduced the total flow volume about 36 percent over a 5-year period. Analyses showed the reduction occurred primarily in the less-than-2.5-cfs flow range, indicating the base flow regime has been altered. However, channelizing the downstream, mild-sloped, 3.6 miles of Tonkawa Creek that flows across a Washita River terrace increased the flow volume fourfold at the outlet. A double-masscurve analysis of water yield from a 1,127-square-mile Washita basin segment versus an untreated tributary showed the yield has not changed after 25 percent of the tributary area had been treated. Therefore, the flow reduction caused by structures is being offset by increased yields from channelization.     

SATELLITE MICROWAVE OBSERVATIONS OF SOIL MOISTURE VARIATIONS1

ABSTRACT: Results from studies in the Illinois-Indiana and Texas-Oklahoma areas indicate that satellite microwave observations at the 1.55 cm wavelength are responsive to relative moisture variations in the near surface layer of the soil. Because significant vegetation cover absorbs the 1.55 cm microwave emission from the soil, the target area must be predominately bare soil or low density vegetation cover for meaningful measurements to result. The 25 km resolution of the satellite sensor limits application of the microwave techniques to large areas such as watersheds or agricultural districts rather than individual fields. In general, at 1.55 cm. there is an inverse relationship between microwave brightness temperature and changes in soil moisture levels (as indicated by antecedent rainfall) in agricultural regions before the planting of crops or during the early growing season when vegetation cover is sparse. Even early season observations should be of great value in deciding on the time and type of crop planting and for initial irrigation scheduling when the root zone is still in close proximity to the surface.     

Metabolic fate of the 14C-labeled herbicide clodinafop-propargyl in soil

The metabolic fate of ¹⁴C-phenyl-labeled herbicide clodinafop-propargyl (CfP) was studied for 28 days in lab assays using a soil from Germany (A_p horizon, silt loam, and cambisol). Mineralization amounted to 12.40% of applied ¹⁴C after 28 days showing a distinct lag phase until day 7 of incubation. Portions of radioactivity extractable by means of 0.01 M CaCl₂ solution (bioavailable fraction) decreased rapidly and were 4.41% after 28 days. Even immediately after application, only 57.31% were extracted with the aqueous solvent. Subsequent extraction using accelerated solvent extraction (ASE; acetonitrile/water 4:1, v/v) released 39.91% of applied ¹⁴C with day 0 and 26.16% with day 28 of incubation from the samples. Non-extractable portions of radioactivity thus, increased with time amounting to 11.99% (day 0) and 65.00% (day 28). A remarkable increase was observed between 14 and 28 days correlating with the distinct increase of mineralization. No correlation was found throughout incubation with general microbial activity as determined by DMSO reduction. Analysis of the CaCl₂ and ASE extracts by radio-TLC, radio-HPLC and GC/MS revealed that CfP was rapidly cleaved to free acid clodinafop (Cf), which was further (bio-) transformed; DT₅₀ values (based on radio-TLC detection of the parent compound) were far below 1 day (CfP) and about 7 days (Cf). TLC analysis pointed to 2-(4-hydroxyphenoxy)-propionic acid as further metabolite. Due to fractionation of non-extractable residues, most of the ¹⁴C was associated with fulvic and humic acids, portions in humin fractions and non-humics were moderate and low, respectively. Using a special strategy, which included pre-incubation of the soil with CfP and then mineralization of ¹⁴C-CfP as criterion, a microorganism was isolated from the soil examined. The microorganism grew using CfP as sole carbon source with concomitant evolution of ¹⁴CO₂. The bacterium was characterized by growth on commonly used carbon sources and by 16S rDNA sequence analysis. The sequence exhibited high similarity with that of Rhodococcus wratislaviensis (99.56%; DSM 44107, NCIMB 13082).     

基于数量化理论Ⅱ的鄂西北山区坡面土壤侵蚀强度评价

水土流失既是资源问题，又是生态环境问题。土壤侵蚀对人类生存和发展构成了严重威胁，成为制约可持续发展的障碍因素。以鄂西北丹江口库区郧西县坡面径流小区为试验点，通过分析小区的实地观测数据，建立坡面土壤侵蚀定性评价指标体系，并将数量化理论II作为有效的数学方法，建立郧西县坡面径流小区土壤侵蚀强度评价模型，对参与建立模型的样本进行回归分析，其准判率达到800%以上，并且利用该模型对其他年份坡面土壤侵蚀强度实测数据进行对比验证，得到土壤侵蚀强度分级的精度较高。研究表明，建立的郧西县坡面径流小区土壤侵蚀强度评价模型有较好的适用性与可靠性，可为郧西县及类似自然地理环境的其他区域水保工作起到一定指导意义     

Managing forest ecosystem services for hydropower production

In many countries, hydropower development is rapidly becoming a focus of green growth policies. This represents a significant opportunity for ecosystem services-based land management that integrates environmental and development goals to benefit the hydropower sector and support economic growth. In this study, we present an approach for targeting ecosystem-provision investment in hydropower catchments coupled with hydrologic modeling to quantify the benefits of soil and water conservation activities. We demonstrate the application of this approach in five hydropower facility catchments in the state of Himachal Pradesh, India. The results show that there is a high potential for targeted soil and water conservation to increase sediment retention services that benefit hydropower facilities (up to a 44% reduction in sediment transported from uplands into streams), although this benefit is distributed non-uniformly across catchments and levels of investment. The extent to which services can be improved is strongly driven by current land use and management practices that impact how and where conservation activities can be located. Iterative use of the method described here, in a process of stakeholder engagement and capacity-building, enables policy makers to determine the optimal mix of land management strategies and budget allocation to maximize service improvements that support hydropower production.     

基于参与式社区评估法的泾河流域景观管理问题分析

参与式社区评估法既兼顾了景观管理中的地理变量,同时还将社会经济因素纳入了考虑范畴,是深入进行问题分析客观有效的方法之一。本文采用参与式社区评估法,运用问题矩阵和问题树分析,对泾河流域景观管理中存在的问题和利益相关者的认知进行了分析。研究发现,绝大多数利益相关者认为土壤侵蚀已成为第一严重的问题,其次是土地生产力低下、自然灾害、植被破坏等。尽管当地公众已经认识到了土壤侵蚀的严重危害,但在安排土地利用方式时,却很少考虑土壤侵蚀带来的危害,仍然从事着自给自足的粮食生产活动。     

A SUPERCRITICAL FLUME FOR MEASURING SEDIMENT-LADEN STREAMFLOW1

ABSTRACT: After 25 years of operation on ephemeral streams in the semiarid Southwest, this supercritical flume has provided more than 350 station-years of reliable streamflow data, even under freezethaw conditions experienced at elevations of 1,500 to 2,100 m, in Arizona. The flume has also provided streamflow data during flood periods produced by high intensity summer thunderstorm conditions, where considerable sediment and other debris was moved downstream.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.