Gold mining is a tremendously important economic activity in rural districts of Ethiopia. We assessed the impacts of artisanal gold mining on soil and woody vegetation in northern Ethiopia. Estimation of soil loss, plant inventory, group discussions and transect studies were used to address the research questions. We employed t‐test to compare woody species and soil loss between mined and unmined sites. Moreover, we ran one‐way ANOVA to compare the average volume of soil loss among the mining sites. The study shows that gold mining removed colossal volumes of soil from the mining landscape with a significant difference among gold mining sites (P ≤ 0.05). Soil loss between the mined and unmined sites was also significant (P ≤ 0.05). Moreover, gold mining destroyed massive tracts of vegetation. Woody species encountered at plot level decreased from artisanal gold mined to unmined sites (P ≤ 0.05). Moreover, dead trees and exposed tree roots were higher in mined than the unmined areas (P ≤ 0.05). This discouraged regeneration and recruitment of woody vegetation. To conclude, gold mining system converted vegetated sites and farmlands into dysfunctional landscape. Therefore, we suggest that combined rehabilitation efforts are required to overcome the challenges of artisanal gold mining on sustainable land management in northern Ethiopia.

Improved slow bolting lettuce variety is one of the important traits of lettuce for farmers in the study area to increase their production and income. Therefore a field experiment was conducted in Enderta district of South eastern zone of Tigray with the objective to evaluate and demonstrate the slow bolting lettuce variety, enhance the income of farmers by increasing production and productivity, and participate in farmers' research group in evaluation and demonstration of varieties. Improved (Tesfa Mekelle) and local (Paris Island) lettuce varieties were used as treatment for demonstration. 20 farmers were selected which have access to irrigation and willingness to participate. Both qualitative and quantitative data were collected. To measure the attitude of farmers towards improved technology, a five-point Likert scale method was used. The data was analyzed using appropriate software. To calculate the gap analysis, technology gap and technology index were used. The results revealed that farmers obtained an average of 412.89 and 283.83 qt ha-1 biomass yield of lettuce from improved and local varieties, respectively. This can clearly show that farmers can increase their lettuce yield and income by 45.5 and 79.5% using the improved variety, respectively. Based on the farmers' perception, the study also showed that farmers were satisfied in all parameters of improved lettuce like adaptability, slow bolting, marketability, tasty, softness of leaves and productivity. Therefore, research center and the offices of agriculture and rural development of the respective districts should take the lead to further popularization of the variety for their respective mandate areas to boost production and productivity of lettuce.

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<p>Soil erosion is a process accelerated by natural and anthropogenic disturbances over time and space, leading to land degradation and causing geomorphological change. It is difficult to investigate the spatial and temporal distribution of soil erosion and sedimentation in data-scare areas, in that case, the use of simplified methods to analyze soil erosion and sediment connectivity variations over time and space can help. Sediment connectivity denotes the transfer of sediment from source to sink areas through channel systems of landscape compartments within a watershed. In this study, we aimed to investigate sediment yield (SY) variation over time and space and understand the link between hillslope soil erosion and sediment connectivity to identify hotspot areas in the Rogativa catchment (∼53 km<sup>2</sup>) in Southeast Spain. The (specific) sediment yield (S)SY was estimated by combining the Revised Universal Soil Loss Equation (RUSLE) model with the sediment delivery ratio (SDR). The SDR was calculated based on the Index of Connectivity (IC). In the channels, 100% delivery was assumed. In the Rogativa catchment, 58 check dams were constructed in 1976/77. Their trapping efficiency, obtained from field observations of sediment retained behind the checkdams in 2003, was included in the SDR estimation of the checkdams. SY was estimated from accumulated hillslope soil erosion in the local stream network while accounting for sedimentation through the SDR. Soil erosion, IC, SDR, and (S)SY were quantified and compared for the years 1956, 1977, 2001, and 2016, for which different land use maps were available. SY model results for the year 2001 were compared with observed SY (in 2003) behind the check dams. Only for about half of the checkdams, model results were comparable. This is investigated further and could be explained by complex sediment dynamics within the channels and between checkdams (i.e. one check dam retaining part of the sediment, the next downstream checkdam as well, etc) – these dynamics are not included in the RUSLE-SDR model. The RUSLE-generated soil erosion and sediment connectivity signatures (IC, SDR, and (S) SY) showed higher values in the channels and croplands than in hillslopes and decreased over time due to significant changes in land use and construction of check dams in the catchment. Moreover, the combined proportion of erosion-connectivity patterns showed about 7% of the area adjacent to some of the streams was found both highly erodible and highly connected, which indicates an adverse erosion-prone part. It is possible to apply this method to understand SY amount and distribution and identify hotspot locations in drainage systems with limited field data in data-scarce semi-arid areas like the Rogativa catchment. However, more field observations to validate the models to identify hotspot locations and investigate river network systems rather than focusing only on hillslopes, which could help to know where to intervene in the catchment.</p> <p>Keywords: Soil erosion-RUSLE, Sediment connectivity, Sediment delivery ratio, Sediment yield, hotspot location</p>

Indigenous knowledge is the local or traditional knowledge system used by farmers. Therefore indigenous knowledge on irrigation water management means using of local or traditional knowledge system to manage irrigation water. This study was aimed to investigate farmers' current irrigation water management practice and their technical performance. In this study I used reconnaissance survey and observation were carried out with each implementing center and Woreda Bureau of Agriculture to obtain overview of different irrigation schemes and irrigation practice conditions. The collected qualitative and quantitative data both from primary and secondary sources were analyzed using appropriated statistical methods like SPSS. The study result showed that farmers have developed several indigenous knowledge of irrigation water management practices. Among these knowledge, most of farmers in both weredas use furrow irrigation method, farmers use soil moisture method and crop leaf wilt techniques to irrigate cropped land, Most farmers apply irrigation water at morning and night time, The respondents uses watering top ridge to determine irrigation water sufficient and watering bottom ridge and slow stream flow for irrigation water insufficient.