**1. Introduction**

Catchment represents a logical administrative unit of governance as a biological, physical, economic and social system, which is affected by natural (rain, sun) and human influences (industry, agriculture, population). The effective implementation of the river basin management plans are necessary and should include clear and strong objectives and instructions for maintaining the quality of surface water, even if needs of the society are changed in the future (Wagner et al., 2002).

The European Union Water Framework Directive (WFD) (2000/60/EC) set new rules for the catchments water management. The main objectives of the WFD are to improve, protect and prevent a further decreasing of water quality and to achieve good quality status of water bodies in Europe by 2015. The lack of studies and data put doubts on ambitious goals as it is difficult to examine the environmental changes associated with nutrients from biology to ecology (Neal & Heathwait, 2005). Volk et al. (2009) showed that to reach the WFD target water quality in German study catchments, dramatically unrealistic socio-economic measures would be needed (reduction of cultivated land from 77% to 46%, 13% of organic farming, increasing pastures from 4% to 15% of the forest from 10% to 21% and wetlands from 0% to 9%. Clean Water Act implemented in 1972 in the USA still did not achieve all objectives for drinking and bathing waters even after more than 30 years (Randhir & Hawes, 2009). Single or uniform integrated catchment management does not meet all the goals in soil and water protection due to usually very heterogeneous catchment characteristics (precipitation, geomorphology, slope, soils, agricultural crops) (Hatch et al., 2001).

Agricultural intensification since 1940 resulted in higher nutrients leaching to water and increased rate of soil erosion. The soil loss with surface migration of soil particles, which exceeds more than 1 t ha-1 year-1 is regarded as irreversible within a time span of 50-100 years (EUSOILS, 2004). In Europe over 54 million km2 of land is suffering similar or a higher rate of loss (Čarman et al., 2007). Erosion can cause significant reduction of the fertile soil depth, a significant loss of nutrients (Ramos & Martinez-Casasnovas, 2006) and depositions of the fine sediment in rivers, affecting fish spawning and egg development (Lohse, 2008).

Nitrogen (N) is an easily available nutrient and to the most crops is the limiting factor in production. Majority of the loss is associated with leaching in to groundwater and minority

Modelling of Surface Water Quality by Catchment Model SWAT 109

through agri-environmental measures and their impacts on quantity and quality of the

The river Reka catchment spreads over 30 km2 and is located in the northwestern part of the country (Goriška Brda) (Fig. 1). Altitude ranges between 75 m and 789 m a.s.l. Very steep ridges of numerous hills, which are directed towards the southwest, characterizes the area. The catchment landscape is very agricultural with higher percentages of forest (56 %) and vineyards (23 %). The river Dragonja catchment area spreads over 100 km2 and is located in the far southwestern part of the country (Istria) (Fig. 1). This is a coastal catchment (Adriatic Sea), with an altitude ranging between 0 and 487 m a.s.l. The ridges of the hills are designed as a plateau with flat tops and steep slopes. The landscape is largely overgrown with forest

(63 %) and grassland (18 %). Steep slopes allow cultivation only on the terraces.

Fig. 1. The river Reka and Dragonja catchment case areas divided in sub-catchments

surface waters.

**2. Materials and methods** 

**2.1 Descriptions of the study areas** 

with surface runoff, depending on the geology and soil type. N leaching occur during wet periods of the year, after crops are harvested, fertilizers and mineralized crop biomass residues are exposed to leaching (Glavan & Pintar, 2010), and when N is not actively absorbed by plants and precipitation exceeds evapotranspiration (Rusjan, 2008).

Phosphorus (P) is known as the limiting factor in eutrophication of freshwater ecosystems (Khan & Ansari, 2005). P is a macronutrient required for the life of all living cells that plants absorb directly in the form of ortho-phosphorus (PO4 3-) (Khan & Ansari, 2005). Excessive use of P fertilizers may lead to P soil saturation, causing P transport with runoff bound to soil particles or through drainage (Bowatte et al., 2006). Most P in inland waters is contributed by point sources (wastewater treatment plants). Due to advances in wastewater, P stripping has put more emphasis on P from agriculture (Buda et al., 2009).

Computer models in modern integrated catchment management are indispensable for studying the levels of pollutants from diffused sources, as they are capable of merging different spatial and environmental data (Dymond et al., 2003; Kummu et al., 2006). Catchment models can be divided into empirical-statistical (GLEAMS, MONERIS, N-LES), physical (WEPP, SA) and conceptual (distributed or partially distributed - SWAT, NL-CAT, TRK, EveNFlow, NOPOLU, REALTA) (Hejzlar et al., 2009; Kronvang et al., 2009a). Models connected with the Geographic Information System (GIS) has gained new values, as they are more accessible and understandable to different target groups.

Agricultural Research Service (ARS) of the U.S. Department of Agriculture is very active in developing models for agricultural hydrology, erosion and water quality. The Soil and Water Assessment Tool (SWAT) model was developed to assist the water managers in examining the impacts of agricultural activities in catchments (Arnold et al., 1998). The SWAT model is widely used for modelling the hydrology in terms of quantity of water (discharge, soil water, snow and water management), quality of water (land use, production technologies, good agricultural practices, agri-environmental measures) and the effects of climate changes (Gassman et al., 2007; Krysanova & Arnold, 2008). This model enables the modelling of long-term (more than 25 years) effects of agri-environmental measures (Bracmort et al., 2006). SWAT model has undergone several refinement and upgrades resulting in different model versions (SWAT2000, SWAT2005 and SWAT2009). The overall desire to adapt the model for the local conditions has resulted in many adaptations like G-SWAT, SWIM, E-SWAT, K-SWAT (Gassman et al., 2007).

The European Commission has, for the purposes of ensuring adequate tools, for the end user, that could meet the current European needs for harmonization and transparency in the quantitative assessment of diffused sources of nutrient losses, financially supported EUROHARP project (Kronvang et al., 2009b). This project compared nine different catchment models for simulation of the non-point sources of pollution from agriculture on numerous catchments in Europe. The results of the project ranked SWAT, along with NL-CAT and TRK models, in the top three of the best (Schoumans et al., 2009). EUROHARP study showed that the modellers are not yet able to propose only on the best and the most appropriate model for all river basins in Europe, because the quality of the models is based on the input data quality along with quality of the modellers (Kronvang et al., 2009a).

The aim of this chapter is to examine modelling of surface water quality by the catchment model Soil And Water Assessment Tool (SWAT). The capabilities of the model were tested through agri-environmental measures and their impacts on quantity and quality of the surface waters.
