Nitrates in Turkish waters: sources, mechanisms, impacts, and mitigation.

Intensive technological developments, rapid population growth and urbanization, and excessive use of nitrogen fertilizers have caused water resources to be contaminated substantially by nitrates in Turkey. The accumulated information should be evaluated to draw a nationwide attention to the problem. The aim of this review article was to highlight the importance of nitrate (NO3) contamination and to discuss the measures to be taken to mitigate the contamination across the nation. Agriculture, especially chemical fertilizers used in irrigated agriculture, was the most important source of NO3 in groundwater. Also, the industrial and domestic discharges substantially contributed to NO3 in both groundwater and surface waters in many cases. The most severe and widespread groundwater (e.g., 344 mg NO3 L-1 in Izmir, 476 mg L-1 in Afyon, 477 mg L-1 in Antalya, and 948.0 mg L-1 in Konya) and surface water contaminations (e.g., 293.8 mg NO3 L-1 in Izmir, 63.3 mg L-1 in Eskisehir, 89.8 mg L-1 in Edirne, and 90.6 mg L-1 in Sakarya) occurred in the regions where intensive agriculture, industrial development, and rapid urbanization were clustered. Well-established irrigation and fertilizer management plans are critical for reducing fertilizer-related NO3 contaminations in the irrigated agriculture. Special attention should be given to the regions where industrially and domestically contaminated running water bodies are in contact with groundwater. Discharge of wastewaters to the streams, creeks, rivers, and lakes should be prevented. Well-designed studies are needed to evaluate potential health effects, including the risk of cancer, of NO3 in drinking water.

A method for calculating land degradation neutrality.

Land degradation neutrality (LDN) has been introduced by United Nations Convention to Combat Desertification (UNCCD). Studies of LDN has been encouraged worldwide by UNCCD to compact land degradation. The LDN aims to maintain or even improve the land quality over time and therefore, it envisages quantifying the balance between the gains and losses within a given land type and scale. In this regard, a mathematical model was developed to calculate and redress land degradation. The calculations showed that the model is stable within the values of quality indices (1 and 2) and correlation coefficients (0 and 1).•The model calculates a proxy parameter as a representative of land quality using a set of land quality indices and correlation coefficients between those indices.•The model compares the values for proxy variable for initial and degraded conditions, and calculates the gains needed to equalize the two values.•The model is independent of scale and it is easy to use.

Seasonal changes of spatial variation of some groundwater quality variables in a large irrigated coastal Mediterranean region of Turkey.

Soil and groundwater degradations have taken considerable attention, recently. We studied spatial and temporal variations of groundwater table depth and contours, and groundwater pH, electrical conductivity (EC), and nitrate (NO3) content in a large irrigated area in Western Mediterranean region of Turkey. These variables were monitored during 2009 and 2010 in previously constructed 220 monitoring wells. We analyzed the data by geostatistical techniques and GIS. Spatial variation of groundwater table depth (GTD) and groundwater table contours (GTC) remained similar across the four sampling campaigns. The values for groundwater NO3 content, EC, and pH values ranged from 0.01 to 454.1 gL(-1), 0.06 to 46.0 dS m(-1) and 6.53-9.91, respectively. Greatest geostatistical range (16,964 m) occurred for GTC and minimum (960 m) for groundwater EC. Groundwater NO3 concentrations varied both spatially and temporally. Temporal changes in spatial pattern of NO3 indicated that land use and farming practices influenced spatial and temporal variation of groundwater NO3. Several hot spots occurred for groundwater NO3 content and EC. These localities should be monitored more frequently and land management practices should be adjusted to avoid soil and groundwater degradation. The results may have important implications for areas with similar soil, land use, and climate conditions across the Mediterranean region.

Spatial variation, mapping, and classification of moss families in semi-arid landscapes in NW Turkey.

Geostatistics and remote sensing techniques are frequently used in analyzing the spatial variability of terrestrial ecosystems. We analyzed spatial variation of moss families by geostatistics and Landsat imagery in a typical semi-arid landscape in North Central Anatolia, Turkey. We sampled 49 sites, chosen based on elevation, slope steepness, and slope aspect. Moss families were determined in a 10-m(2) representative area at each sampling site. The samples were transported to a laboratory and identified for moss families. In total, 10 families were found. Semivariogram analysis was performed to analyze the spatial structure of these families. The semivariogram analysis showed that the moss families were spatially dependent within 117 m in the study area. Thirteen thematic classes were categorized by Landsat Thematic Mapper (TM) image in the study area. The classification resulted in an overall kappa statistic of 0.8535, producer accuracy of 74.29, and user accuracy of 86.67. The family with the lowest classification accuracy was Orthotrichaceae (kappa of 0.6379, producer accuracy of 64.52, and user accuracy of 66.67). The moss families and the other classes were identified with a 0.78 kappa statistic value and an 80.74 % accuracy level by using the Landsat TM. The classification showed that Brachytheciaceae, Pottiaceae, Bryaceae, and Grimmiaceae were the most abundant moss families in this semi-arid environment.

Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey.

Information on the potential risk for soil salinity buildup can be very helpful for soil salinity management in irrigated areas. We evaluated the spatial and temporal variability of groundwater salinity (GWS) and groundwater depth (GWD), which are two of the most important indicators of soil salinity, by indicator kriging technique in a large irrigated area in northern Turkey. GWS and GWD were measured on a monthly basis from irrigation season (August 2003) to rainy season (April 2004) at 60 observation wells in the 8,187-ha irrigated area. Five indicator thresholds were used for GWS and GWD. The semivariogram for each of the thresholds for both variables was analyzed then used together with experimental data to interpolate and map the corresponding conditional cumulative distribution functions (CCDF). Risk for soil salinity buildup was greater in the irrigation season compared to that in the rainy season. The greatest risk for soil salinity buildup occurred in the eastern part of the study area, suffering from poor drainage problem due to malfunctioning drainage infrastructure, as indicated by the CCDF of GWS and GWD obtained in both seasons. It was concluded that a combination of mechanical and cultural measures should be taken in high-risk locations to avoid further salinity problems.

Modeling nitrogen uptake and potential nitrate leaching under different irrigation programs in nitrogen-fertilized tomato using the computer program NLEAP.

Readily available nitrogen (N) sources such as ammonium nitrate with excessive irrigation present a potential hazard for the environment. The computer program Nitrate Leaching and Economic Analysis Package (NLEAP) is a mechanistic model developed for rapid site-specific estimates of nitrate-nitrogen (NO3-N) moving below the root zone in agricultural crops and potential impacts of NO3-N leaching into groundwater. In this study, the value of NLEAP was tested to simulate N uptake by crops and NO3-N leaching parameters in large lysimeters under the tomato crop. Three seedlings of tomato variety of H-2274 (Lycopersicum esculentum L.) were transplanted into each lysimeter. N fertilizer at the rate of 140 kg N ha(-1) was sidedressed in two split applications, the first half as ammonium sulphate and the second half as ammonium nitrate. The lysimeters were irrigated based on programs of C 0.75, 1.00, 1.25 and 1.50, C referring to class A-Pan evaporation coefficients. Parameters such as leaching index (LI), annual leaching risk potential (ALRP), N available for leaching (NAL), amount of NO3-N leached (NL) and amount of N taken up by the crops (NU) were estimated using the NLEAP computer model. To test the ability of model to simulate N uptake and NL, measured values were compared with simulated values. Significant correlations, R2 = 0.92 and P < 0.03 for the first year and R2 = 0.86 and P < 0.06 for the second year, were found between measured and simulated values for crop N consumption, indicating that the NLEAP model adequately described crop N uptake under the varied irrigation programs using an optimal N fertilization program for the experimental site. Significant correlations, R2 = 0.96 and P < 0.01 for the first year and R2 = 0.97 and P < 0.01 for the second year, were also found between measured and simulated values of NL, indicating that the NLEAP model also adequately predicted NL under the varied irrigation programs. Therefore, this computer model can be useful to estimate the NO3-N moving beyond the root zone under conditions in which the present experiment was carried out. Also, the NLEAP-estimated NAL values and other parameters can also be used to improve N management practices and N fertilizer recommendations that will help to decrease the adverse effect of N fertilizer on groundwater quality and farm profitability.