SOIL EROSION AWARENESS AND USE OF CONSERVATION TILLAGE FOR WATER QUALITY CONTROL1

Water pollution through loss of topsoil from farmland continues to be a major problem, despite nearly 50 years of providing farmers technical and financial assistance for soil and water conservation. The technology for controlling erosion and water pollution is available, but farmers have been slow in implementing control practices. Past research has shown that farmers tend to be unaware of the seriousness of the erosion problem on their own operations. Using a random sample of farmers from central Iowa, the relationship is examined between awareness of a soil erosion problem and the use of conservation tillage. Results indicate that awareness of a soil erosion problem effects the use of conservation tillage, and that awareness can be enhanced by experiential educational strategies such as the development and implementation of a soil and water conservation plan.     

EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY1

ABSTRACT: Few studies have been conducted to explore the effects of initial abstraction on estimated direct runoff despite the widespread use of the curve number (CN) method in many hydrologic models to estimate direct runoff. In this study, use of a 5 percent ratio of initial abstraction (I_a) to storage (S) to estimate daily direct runoff with modified CN values for a 5 percent I_a/S value was investigated using the Long‐Term Hydrologic Impact Assessment (L‐THIA) geographic information system (GIS). In addition, the effects on estimated runoff of altering the hydrologic soil group due to urbanization were investigated. The L‐THIA model was applied to the Indiana Little Eagle Creek watershed with 5 percent and 20 percent I_a/S values, considering hydrologic soil group alteration due to urbanization. The results indicate that uses of a 5 percent l_a/S and modified CN values and Hydrologic Soil Group D for urbanized areas in model runs can improve long term direct runoff prediction.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

SOIL SALINITY PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site.     

USING SOIL TEXTURE TO ESTIMATE SATURATED HYDRAULIC CONDUCTIVITY AND THE IMPACT ON RAINFALL-RUNOFF SIMULATIONS1

ABSTRACT: In this paper a new set of soil texture data is used to estimate the spatial distribution of saturated hydraulic conductivity values for a small rangeland catchment. The estimates of conductivity are used to re-excite and re-evaluate a quasi-physically based rainfall-runoff model. The performance of the model is significantly reduced with conductivity estimates gleaned from soil texture data rather than the infiltration data used in our previous efforts.     

LANDSAT MID-INFRARED DATA AND GIS IN REGIONAL SURFACE SOIL-MOISTURE ASSESSMENT1

ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended.     

SPATIAL DISTRIBUTION OF POINT SOIL MOISTURE ESTIMATES USING LANDSAT TM DATA AND FUZZY-C CLASSIFICATION1

ABSTRACT: Many hydrologic models have input data requirements that are difficult to satisfy for all but a few well-instrumented, experimental watersheds. In this study, point soil moisture in a mountain watershed with various types of vegetative cover was modeled using a generalized regression model. Information on sur-ficial characteristics of the watershed was obtained by applying fuzzy set theory to a database consisting of only satellite and a digital elevation model (DEM). The fuzzy-c algorithm separated the watershed into distinguishable classes and provided regression coefficients for each ground pixel. The regression model used the coefficients to estimate distributed soil moisture over the entire watershed. A soil moisture accounting model was used to resolve temporal differences between measurements at prototypical measurement sites and validation sites. The results were reasonably accurate for all classes in the watershed. The spatial distribution of soil moisture estimates corresponded accurately with soil moisture measurements at validation sites on the watershed. It was concluded that use of the regression model to distribute soil moisture from a specified number of points can be combined with satellite and DEM information to provide a reasonable estimation of the spatial distribution of soil moisture for a watershed.     

GROUND-WATER RECHARGE THROUGH ACTWE SAND DUNES IN NORTHWESTERN NEVADA1

ABSTRACT: Most water-resouree investigations in semiarid basins of the Great Basin in western North America conclude that ground-water recharge from direct precipitation on the valley floor is negligible. However, many of these basins contain large areas covered by unvegetated, active sand dunes that may act as conduits for ground-water recharge. The potential for this previously undocumented recharge was investigated in an area covered by sand dunes in Desert Valley, northwestern Nevada, using a deep percolation model. The model uses daily measurements of precipitation and temperature th determine energy and moisture balances, from which estimates of long-term mean annual recharge are made. For the study area, the model calculated a mean annual recharge rate of as much as 1.3 inches per year, or 17 percent of the long-term mean precipitation. Model simulations also indicate that recharge would be virtually zero if the study area were covered by vegetation rather than dunes.     

毕节地区各土类水土保持树种的Fuzzy评价

根据毕节地区16个主要造林树种的生态生物学特性,结合本区气候和土壤生态条件,运用 Fuzzy 二级评价模型,对各土类水土保持树种的适宜程度进行了综合评价。     

天然黏土材料附着纳米TiO2对 电解锰渣中锰的吸附固定

采用机械球磨法对膨润土、硅藻土、高岭土3种天然黏土材料进行预处理,通过超声法将纳米TiO_2附着于其上制得复合材料,考察了不同复合材料加入量及养护时间条件下复合材料对电解锰渣中Mn的吸附固定效果。3种天然黏土材料中,硅藻土的平均粒径最小,比表面积和总孔隙度最大,对水中Mn的吸附量也最大。黏土材料附着纳米TiO_2后对电解锰渣中Mn的吸附固定效果较单纯黏土材料有明显改善。在养护时间为12 d、硅藻土附着纳米Ti O_2复合材料加入量为10%(w)的最佳条件下,Mn的TCLP浸出量较原电解锰渣下降了83.04%。