ABSTRACT
Soil erosion significantly affects agricultural production. Soil and Water Conservation (SWC) measures have been constructed to reduce soil loss. However, the impact of SWC measures on physicochemical soil properties has rarely been investigated in most parts of Ethiopia. Therefore, this study was designed to evaluate the effects of SWC measures on selected soil physicochemical properties in the Jibgedel watershed, West Gojjam zone, Ethiopia. The study also assessed the farmers' perception of the benefits and impacts of SWC measures. Composite and core soil samples were taken at a depth of 0 to 20 cm from four farmlands with SWC measures (soil bund, stone bund, and soil bund with sesbania tree) and without SWC measures in three replications. Results have shown that employing SWC measures in the farmland significantly improved most of the physicochemical properties of the soil compared to farmland without SWC measures. Bulk density from soil bund with and without sesbania trees was significantly lower than stone bund and untreated farmland. Soil organic carbon, total nitrogen, electrical conductivity, and available phosphorus from soil bund with sesbania tree were significantly higher than other treatments. The result also revealed that most farmers perceived that the implemented SWC measures improved soil fertility and crop yield. SWC measures are easier to adopt for integrated watershed management when farmers are well-versed in them.
Subject(s)
Conservation of Water Resources , Sesbania , Soil , Ethiopia , Carbon , Environmental Monitoring , TreesABSTRACT
The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.
