Investigation of the relationship of groundwater quality and irrigation: the case of Mardin Kiziltepe Plain (Mesopotamia) in Turkey.

Underground water resources are one of the most valuable vital resources for mankind. Groundwater is used as drinking water and for agricultural irrigation. However, in recent years, it has been exposed to dangerous pollution, mainly due to man-made reasons. The study area is located in the Upper Mesopotamian region, where dry agriculture has been practiced since ancient times, which has semi-arid characteristics and where important civilizations lived. In this direction, the changes in groundwater quality were investigated with seasonal, annual samples taken from selected wells in Mardin Kiziltepe Plain in Upper Mesopotamia region and representing the plain in general and were subjected to water quality classifications. Statistical analyses were carried out on EC and NO3- parameters, which are important in determining the quality of groundwater. The results obtained were interpreted, evaluated in terms of drinking and agricultural uses, and it was observed that there were no non-standard values. In addition, the study area will be opened for irrigation in the near future within the framework of GAP, the largest integrated irrigation project in Turkey. This study, which is the first scientific research to be carried out before intensive irrigation, will be the first memory that will provide a very important data set for the region and will be recorded. In addition, the results of the study will be the basis for the comparison of the research to be carried out after the transition to irrigated agriculture depending on the GAP and the pre-irrigation data.

Post-irrigation degradation of land and environmental resources in the Harran plain, southeastern Turkey.

Irrigation is a key factor in plant production systems. However, excessive and inappropriate water and soil management systems can cause significant environmental problems. The GAP (the Southeastern Anatolia Project, SEAP) is a multisectoral integrated regional development project. It aims to improve the economical and social welfare of the region as best as possible. The two main objectives of the GAP project include irrigation and energy production. Irrigation was introduced to the Harran plain in 1995, and it led to significant changes in the land use patterns. The use of high-yielding crop varieties and chemical inputs (fertilizers and pesticide usage) resulted in important increases in plant production. Conversely, there was also an increase in land mismanagement. This included practices such as excessive irrigation, intensive soil tillage, insufficient carbon, and soil nutrient cycling. These mismanagement practices lead to soil degradation, which in turn causes increased salinity in soil and groundwater, sediment and nutrient transportation with runoffs, soil erosion, contamination of surfaces and subsurface water sources with nitrates and pesticides, and greenhouse gas emissions. In order to balance yield losses due to the decreasing soil quality, fertilizers and other chemicals were used extensively. This considerably contributed to the environmental problems. Additionally, increasing welfare and population propagated urbanization on arable lands, i.e., the construction of houses, factories, and other agricultural facilities. This further degraded the land and the environment. In conclusion, land irrigation led to production increases, but at the expense of degradation in the environment and soil quality. Moreover, land degradation occurred and further degraded the environment. It is extremely important to improve soil and water management in order to minimize these impacts. The forementioned problems could be solved by improving irrigation efficiencies, good soil and water management strategies, formation of modern well-managed irrigation districts, and educating farmers. Agricultural subsidy-based sanctions could enable these solutions. This study used archived data and evaluations of earlier studies to examine important agroenvironmental influences of introducing irrigation in the Harran plain.

Modeling seasonal variations of long-term soil CO2 emissions in an orchard plantation in a semiarid area, SE Turkey.

Emissions of soil CO2 under different management systems have a significant effect on the carbon balance in the atmosphere. Soil CO2 emissions were measured from an apricot orchard at two different locations: under the crown of trees (CO2-UC) and between tree rows (CO2-BR). For comparison, one other measurement was performed on bare soil (CO2-BS) located next to the orchard field. Analytical data were obtained weekly during 8 years from April 2008 to December 2016. Various environmental parameters such as air temperature, soil temperature at different depths, soil moisture, rainfall, and relative humidity were used for modeling and estimating the long-term seasonal variations in soil CO2 emissions using two different methods: generalized linear model (GLM) and artificial neural network (ANN). Before modeling, data were randomly split into two parts, one for calibration and the second for validation, with a varying number of samples in each part. Performances of the models were compared and evaluated using means absolute of estimations (MAE), square root of mean of prediction (RMSEP), and coefficient of determination (R2) values. CO2-UC, CO2-BR, and CO2-BS values ranged from 11 to 3985, from 9 to 2365, and from 8 to 1722 kg ha-1 week-1, respectively. Soil CO2 emissions were significantly correlated (p < 0.05) with some environmental variables. The results showed that GLM and ANN models provided similar accuracies in modeling and estimating soil CO2 emissions, as the number of samples in the validation data set increased. The ANN was more advantageous than GLM models by providing a better fit between actual observations and predictions and lower RMSEP and MAE values. The results suggested that the success of environmental variables for estimations of CO2 emissions using the two methods was moderate.

Assessment of the quality of the Harran Plain soils under long-term cultivation.

Soil quality refers to the ability of soils to perform their functions well. The soils of the Harran Plain, Turkey, have been put into intensive crop production with the introduction of an irrigation scheme and become increasingly degraded due to unsustainable management and cropping systems that resulted in the loss of production potential. The goal of this study was to quantify the quality of common soil series in the Plain using soil quality indexes (SQI) and to compare SQIs of two long-term crop rotations, cotton and wheat-corn cultivation, and different soil types. Over 400 samples were collected at a 0- to 30-cm depth and analyzed for 31 soil variables. The best representative soil quality variables forming a minimum data set (MDS) were selected using principal component analysis (PCA), and soil quality scores were obtained using both linear and non-linear scoring functions. The MDS included three physical (hydraulic conductivity, bulk density, and plant available water content), two biological (soil organic matter and catalase enzyme activity), and nine chemical soil quality indicators (CEC, pH, plant available Cu and Fe, exchangeable Na and K, soluble Ca, Mg, and Na). Because of the low level of SOM, soil qualities were overall low with indexes obtained using two scoring functions ranging from 38.0/100 to 48.7/100. Correlations between SQI obtained using two approaches (linear vs. non-linear; r > 0.61) and using two data sets (all data vs. MDS; r > 0.79) were high. Non-linear scoring functions were more sensitive to management impacts. ANOVA models testing the individual impacts of soil types and crop management on soil quality were statistically different (p < 0.01), but the models including interactions were not. Overall, the fields under cotton cultivation were generally associated with higher clay contents and had the lowest SQIs as a result of intensive cultivation.