Effect of deforestation on fertility attributes of Mollisols in the NW of Iran

The impacts of deforestation on soil fertility indices – are still not well understood in the forest lands of Iran characterised by Mediterranean type climate. Consistent with this, 8 soil pedons and 32 soil cores were described and sampled from four different soil types of forest and adjacent cultivated soil along a Mollisols transect. The results revealed a considerable depletion in the values of soil organic carbon (by 60–88%), total N (by 67–88%), available K (by 20–45%), cation exchange capacity (by 9–21%), and the diethylene-triamine pentaacetic acid (DTPA) fraction of Fe (by 40–72%), Mn (by 10–60%), and Zn (by 49–80%) after deforestation. In contrast, soil pH (by 0.36–0.9 units), C:N ratio (by 3–84%), available P (22–139%), and DTPA Cu (by 4–55%) tended to increase due to deforestation. Cultivated soils showed a drop of 70–82% in the values of the soil productivity index than to those of the forest soil, indicating a degrading and declining effect of deforestation on soil productivity capacity. It was found that the majority of soil fertility indices were affected negatively by deforestation and more than half of the organic matter was lost to deforestation, which, in turn, could lead to deterioration in soil quality or land productivity capacity.     

Current Levels and Management of Solid Wastes in Nigeria

Solid waste is of serious concern in developing countries because of its high rate of generation and the low‐end quality of its management. Inefficient handling of solid wastes may result in deterioration of environmental quality, but it can also result in loss of potential resources. This study reviews current solid waste generation and management in Nigeria and the need for an effective collection, recovery, and recycling policy. Our review is based on literature searches and personal field surveys. Observations showed that uncontrolled electronic waste (e‐waste), agricultural‐waste (agro‐waste), scrap metals, waste polymers, and waste from the transportation sector are prevalent in Nigeria. Recent collection rates were less than 50% of the total solid waste generated (i.e., approximately 40% was collected). With an effective collection system and appropriate policies, the abundance of solid waste in the country could present material recovery and recycling opportunities that would boost the economy and move Nigeria closer to sustainable resource management.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Drought,water access,and urban agriculture: a case study from Silicon Valley

In California, the growing popularity of urban agriculture (UA) has unfolded against a backdrop of historic drought. While UA is often celebrated as an urban sustainability strategy, it must be able to persist during drought if it is to perform these functions. Using Santa Clara County – the geographic core of Silicon Valley – as a case study, we use interviews and surveys to explore the implications of drought for UA. We show how developing an understanding of water access for UA during a drought requires examining the social and institutional context of water management and use. In metropolitan California, the highly decentralised water supply system combined with the diverse institutional arrangements that support UA create an uneven landscape of water access. Consequently, the pressure to change water-consuming practices – that is, the stress that institutional drought responses place on different water users – is geographically and socially differentiated. Among UA water users, responses to drought have also varied, in part because the possibilities for change are constrained by the sociotechnical arrangements of UA sites and the different purposes of UA.     

A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays

The power-voltage (P-V) characteristic curves of a PV array are nonlinear and have multiple peaks under partially shaded conditions (PSCs). This paper proposes a novel maximum power point tracking (MPPT) method for a PV system with reduced steady-state oscillation based on a two-stage particle swarm optimization (PSO) algorithm. The grouping method of the shuffled frog leaping algorithm (SFLA) is incorporated in the basic PSO algorithm (PSO-SFLA), ensuring fast and accurate searching of the global extremum. An adaptive speed factor is also introduced into the improved PSO to further enhance its convergence speed. Test results show that the proposed method converges in less than half the time taken by the conventional PSO method, and the power is improved by 33% under the worst PSCs, which confirms the superiority of the proposed method over the standard PSO algorithm in terms of tracking speed and steady-state oscillations under different PSCs.     

Climate impact on agroeconomy in semiarid region of Armenia

With 21 % of gross domestic product (GDP) in agricultural sector and having consistently experienced natural disasters (e.g., drought, flood), Armenia is very vulnerable to climate and its change. Given the fact that 63 % of the entire land is planted with grains, this study primarily focuses on the market for wheat flour and bread. Economic welfare loss due to drought episodes is calculated using the economic data integrated with climate measures. Economic data are utilized for the period 1995–2011 (obtained from Statistical Office of Armenia) and specifically include the quantity produced and consumed of wheat flour and bread combined with mean prices, population income, GDP in the agricultural sector, GDP in the planting sector, and governmental expenditure on subsidies. Climate data include temperature and precipitation during the period 1966–2011 (obtained from National Hydrometeorological Service of Armenia). The analysis includes three main components. The first utilizes a market framework that analyzes the impact of climate on equilibrium prices and quantities as well as trade and tax effects. The second employs a logarithmic utility function to estimate the effective insurance policy for the agricultural sector using risk management strategies. Lastly, a macroeconomic model has been developed to assess the efficient sum of governmental expenditure on subsidies and irrigation during the drought episodes and during the mean climatic conditions. All three parts of the study are developed for the first time.