EVAPOTRANSPIRATION DYNAMICS AT AN ECOHYDROLOGICAL RESTORATION SITE: AN ENERGY BALANCE AND REMOTE SENSING APPROACH1

ABSTRACT: Little work is reported where spatial methods are employed to monitor evapotranspiration (ET) changes as a result of vegetation and wetland restoration. A remote sensing approach with the Surface Energy Balance Algorithm for Land (SEBAL) for estimating ET at The Nature Conservancy's Glacial Ridge prairie‐wetland restoration site in northwestern Minnesota is presented. The calibrated 24‐hour ET from SEBAL was estimated with an average error of prediction of ?4.3 percent. Monthly, interseasonal, and seasonal ET for the period of June to September (2000 to 2003) from three adjacent land‐uses: a hydrologic control preserved wetland; a treated or restored site; and a nontreated or impacted wetland, were used in the study. Results from comparing ET behavior to the preserve suggest restoration efforts have affected monthly and seasonal ET within the treated site. Spatial average standard deviations of the seasonal ET within the preserve, treated, and nontreated sites give 47.3, 75.7, and 109.9 mm, respectively, suggesting hydrologic stabilization within the treated site. Monthly and interseasonal comparisons show similar behavior to that of the seasonal data, where monthly correlations suggest increasing agreement within the treated site, approaching those within the preserve.     

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.     

Modeling long-term attainable soil organic carbon sequestration across the highlands of Ethiopia

Environment, Development and Sustainability - The objectives of this study across the highlands of Ethiopia were: (i) to characterize the association between soil organic carbon (SOC) stocks and...     

Long-Term Indigenous Soil Conservation Technology in the Chencha Area,Southern Ethiopia: Origin,Characteristics, and Sustainability

The purpose of this study is to examine the origin, development, and characteristics of terraces (kella), plus their potentials and determinants for sustainable use in the Chencha–Dorze Belle area of southern Ethiopia. Field surveys were conducted to determine the various parameters of the indigenous terraces and in order to collect samples for radiocarbon dating. To identify farmers’ views of the terrace systems, semi-structured interviews and group discussions were also carried out. Terraces were built and used—as radiocarbon dating proves—at least over the last 800 years. The long-term continued usage of the indigenous terraces is the result of social commitments, the structural features of the terraces, and the farmers’ responses to the dynamics of social and cultural circumstances. We dubbed that the terraces are a success story of fruitful environmental management over generations. Thus, a strong need is to preserve and develop this important cultural heritage and example of sustainable land use.     

STORM RUNOFF PREDICTION BASED ON A SPATIALLY DISTRIBUTED TRAVEL TIME METHOD UTILIZING REMOTE SENSING AND GIS1

ABSTRACT: In this study, remotely sensed data and geographic information system (GIS) tools were used to estimate storm runoff response for Simms Creek watershed in the Etonia basin in northeast Florida. Land cover information from digital orthophoto quarter quadrangles (DOQQ), and enhanced thematic mapper plus (ETM+) were analyzed for the years 1990, 1995, and 2000. The corresponding infiltration excess runoff response of the study area was estimated using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service Curve Number (NRCS‐CN) method. A digital elevation model (DEM)/GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. A comparison of predicted to observed stream response shows that the model predicts the total runoff volume with an efficiency of 0.98, the peak flow rate at an efficiency of 0.85, and the full direct runoff hydrograph with an average efficiency of 0.65. The DEM/GIS travel time model can be used to predict the runoff response of ungaged watersheds and is useful for predicting runoff hydrographs resulting from proposed large scale changes in the land use.     

Water Quality Changes as a Result of Coalbed Methane Development in a Rocky mountain Watershed1

Abstract: Coalbed methane (CBM) development raises serious environmental concerns. In response, concerted efforts have been made to collect chemistry, salinity, and sodicity data on CBM produced water. However, little information on changes of stream water quality resulting from directly and/or indirectly received CBM produced water is available in the literature. The objective of this study was to examine changes instream water quality, particularly sodicity and salinity, due to CBM development in the Powder River watershed, which is located in the Rocky Mountain Region and traverses the states of Wyoming and Montana. To this end, a retrospective analysis of water quality trends and patterns was conducted using data collected from as early as 1946 up to and including 2002 at four U.S. Geological Survey gauging stations along the Powder River. Trend analysis was conducted using linear regression and Seasonal Kendall tests, whereas, Tukey’s test for multiple comparisons was used to detect changes in the spatial pattern. The results indicated that the CBM development adversely affected the water quality in the Powder River. First, the development elevated the stream sodicity, as indicated by a significant increase trend of the sodium adsorption ratio. Second, the development tended to shrink the water quality differences among the three downstream stations but to widen the differences between these stations and the farthest upstream station. In contrast, the development had only a minor influence on stream salinity, as indicated by that the stream electrical conductivity exhibited either no trend or a marginally significant positive trend. Hence, the CBM development is likely an important factor that can be managed to lower the stream sodicity. The management may need to take into account that the effects of the CBM development were different from one location to another along the Powder River.     

MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.     

Coffee husk composting: An investigation of the process using molecular and non-molecular tools

Various parameters were measured during a 90-day composting process of coffee husk with cow dung (Pile 1), with fruit/vegetable wastes (Pile 2) and coffee husk alone (Pile 3). Samples were collected on days 0, 32 and 90 for chemical and microbiological analyses. C/N ratios of Piles 1 and 2 decreased significantly over the 90 days. The highest bacterial counts at the start of the process and highest actinobacterial counts at the end of the process (Piles 1 and 2) indicated microbial succession with concomitant production of compost relevant enzymes. Denaturing gradient gel electrophoresis of rDNA and COMPOCHIP microarray analysis indicated distinctive community shifts during the composting process, with day 0 samples clustering separately from the 32 and 90-day samples. This study, using a multi-parameter approach, has revealed differences in quality and species diversity of the three composts.     

Factors influencing scaling up of agroforestry-based spatial land-use integration for soil fertility management in Arsamma Watershed,Southwestern Ethiopian Highlands

This study was set to examine factors influencing agroforestry upscaling, inter-plot natural fertilizer transfer and inter-plot income flow in Arsamma watershed. A semi-structured questionnaire was used to gather necessary information. Contingency table, chi-square, Phi and Cramer's V were used to analyze the data. Access to seedlings was the most important determinant of agroforestry upscaling; and farmers' production orientation, farm size and wealth status ranked, respectively, second, third and fourth. Inter-plot natural fertilizer transfer was primarily influenced by participation in agricultural extension. Wealth status and livestock size ranked, respectively, second and third in influencing inter-plot natural fertilizer transfer. The study indicated a geographic concept of spatial land-use integration for soil fertility management and key factors influencing agroforestry-based land-use integration. Agroforestry-centered diversified small-scale agricultural commercialization, tree-crop-livestock integration, agricultural extension services promotion and multi-purpose tree species supply are the way out to upscale agroforestry and agroforestry-based spatial land-use integration.