Surface water contamination can often be reduced by passing runoff water through perennial grass filters. Research was conducted in 2006 to 2008 to evaluate the size of cool season grass filters consisting primarily of tall fescue (Festuca arundinacea Schreb) with some orchard grass (Dactylis glomerata L.) relative to drainage area size in reducing runoff sediment and phosphorus (P). The soil was Pohocco silt loam Typic Eutrochrepts with a median slope of 5.5 %. The grass filters occupying 1.1 and 4.3 % of the plot area were compared with no filter with four replications. The filters were planted in the V-shaped plot outlets which were 3.7x11.0 m in size. The filter effect on sediment and P concentration was determined from four natural runoff events when nearly all plots had runoff. Filter effect on runoff volume and contaminant load was determined using total runoff and composites of samples collected from 12 runoff events. Sediment concentration was reduced by 25 % with filters compared with no filter (from 1.10 to 1.47 gL(-1)), but P concentration was not affected. The 1.1 and 4.3 % filters, respectively, compared with having no grass filter, reduced: runoff volume by 54 and 79 %; sediment load by 67 and 84 % (357 to 58 kgha(-1)); total P load by 68 and 76 % (0.58 to 0.14 kgha(-1)); particulate P (PP) load by 66 and 82 % (0.39 to 0.07 kgha(-1)); and dissolved reactive P (DRP) load by 73 and 66 % (0.2 to 0.07 kgha(-1)), respectfully. A snowmelt runoff event had 56 % greater DRP concentration compared with rainfall-induced runoff events. Grass filters reduced sediment and P load largely by reducing runoff volume rather than reducing concentration. Well-designed and well-placed grass filters that occupy 1.0 to 1.5 % of the drainage area and intercept a uniform flow of runoff from a drainage area can reduce sediment and nutrient loss in runoff by greater than 50 %.

The main objective of this study is to estimate the total economic loss due to inefficient use of irrigation water in Tunisia. Several approaches have been used for this purpose. The optimal level of water application for different crops is calculated using the actual crop evapotranspiration which is based on FAO-56 method. The residual imputation and yield comparison methods have been used to estimate the economic value of irrigation water for different irrigated crops in different bioclimatic areas. For the empirical analysis, primary data were obtained from a series of surveys that covered 78% of the total irrigated areas and were collected within the framework of the BVirtual Water and Food Security in Tunisia project^ (2013–2015). Secondary data about land distribution of crops in Tunisia were taken from the Ministry of Agriculture (2016). Around 724 farms were randomly sampled considering their bioclimatic area, farm type, and production system. The survey included the main 20 crops produced in Tunisia. Results show that most of farmers are either under or over utilizing irrigation water. The value of total direct economic losses, at the country level, of both types of water inefficiencies, was estimated to around 470 million Tunisian Dinars. Therefore, an improvement of water use efficiency at field level through dissemination of information/knowledge on irrigation scheduling and crop water requirements by extension services to farmers is needed to reduce this huge economic loss, reach higher sustainability in water use and improve food security.

Global change and demographic changes increasingly cause water, food, and health problems at many places of the world. In addition, the growth in bioenergy production leads to land-use change and associated environmental impacts. This Special Issue addresses many of the challenges of agri-cultural, water and nonpoint source pollution management at the watershed scale. In this regard, the Soil and Water Assessment Tool (SWAT) model (Arnold et al., 1998; Arnold and Fohrer, 2005) has proven to be an effective mechanism for assessing water resource and nonpoint source pollution problems for a wide range of scales and environmental conditions across the globe (Gassman et al., 2007). The model is a continuation of nearly 30 years of research efforts by the USDA Agricultural Research Service (ARS). SWAT continues to evolve as users determine needed improvements that will enable more accurate simulation of currently supported processes and new functionalities that will expand the SWAT simulation domain, reflecting the above mentioned challenges.

This is the second part of a Special Issue on developments and applications of the Soil and Water Assessment Tool (SWAT) related to agricultural water and nonpoint source pollution management at a watershed scale (see Volk et al., 2016 for part I).