Geostatistical analysis of a water well field for determination of land management constraints

Soil spatial variability and heterogeneity is a tough but very important matter in the field-scale description of soil properties, such as soil electrical conductivity, soil saturated hydraulic conductivity, and soil salinity. Geostatistics is a useful tool to study spatial distribution of soil properties and optimum sampling strategies in field. Estimating soil salinity, EC and Ks is a vital issue in soil fertility and management. Geostatistical methods, kriging and cokriging, were applied to estimate spatial distributions of the variables that were collected from a large size water well field for the surface soil, rather than entire bore-hole profile of the soil. The results suggested that estimation can be improved using cokriging , rather than kriging. Comparing to kriging results, cokriging reduced the mean squared error and improved the estimation of EC by 2-100% depending on cross-correlated variables. Using the cokriging prediction maps of the soil properties, the soil can be managed cell by cell with prescribed appropriate management strategies such as irrigation and manure application to mitigate soil salinity in the region

Using Geographic Information Systems and Multi-Criteria Decision Analysis to Determine Appropriate Locations for Rainwater Harvesting in Erbil Province, Iraq

Water scarcity is a prominent consequence of global climate change, presenting a significant challenge to the livelihoods of wide parts of the world, particularly in arid and semi-arid regions. This study focuses on Erbil Province in Iraq, where the dual effects of climate change and human activity have significantly depleted water resources in the past two decades. To address this challenge, rainwater harvesting (RWH) is explored as a viable solution. The purpose of this study is to make a suitability zone map that divides the study area into several classes based on the features of each area and its ability to collect rainwater. The map will then be used to find the best place to build different RWH structures. Seven different layers are used to make the RWH suitability zone map: rainfall, runoff, land use/cover (LU/LC), soil texture, slope, drainage density, and the Topographic Wetness Index (TWI). Each layer was assigned specific weights through the Analytical Hierarchy Process (AHP), considering its relevance to RWH. Results revealed four suitability classes: very highly suitable 1583.25 km2 (10.67%), highly suitable 4968.55 km2 (33.49%), moderately suitable 5295.65 km2 (35.69%), and lowly suitable 2989.66 km2 (20.15%). Notably, the suitability map highlights the northern and central regions as particularly suitable for RWH. Furthermore, the study suggested three suitable locations for constructing medium dams, six for check dams, and twenty-seven for farm ponds, according to the requirements of each type. These findings provide valuable insights for the strategic planning and effective management of water resources in the study area, offering potential solutions to the pressing challenges of water scarcit

Urban Expansion Trends, Prediction and Its Impact on Agricultural Lands in Erbil Using GIS and Remote Sensing

The surrounding agricultural lands in the city have been decreasing daily due to the expansion of urbanisation above it and the increase in the urbanisation rate in the study area, as the population growth exerted increasing pressures on the city. Furthermore, the increase in population increases the demand for land for housing and other human services, which will impact agricultural lands. In addition, the lack of proper planning in the city contributes to expanding urbanisation at the expense of agricultural land. This study aims to study the urban expansion in the direction of agricultural lands in Erbil from the year 2000 until 2020, reveal the reasons for the urban expansion in the city and put an end to the trespassers on the lands and it has negative impact on the lack of agricultural areas and the encroachment of urbanisation on it. Landsat TM 5 and Landsat 8 OLI will be used to identify and develop urban growth and its impacts on agriculture and some Remote sensing Data and GIS from 2000 to 2020 with 10 years difference to find the changes in these years and also provide a predicted map for Erbil governorate. The study recommended the necessity of preparing a strategic plan for the use of agricultural lands that regulates the urban development process of the population centres and achieves the appropriate and sustainable use of agricultural lands and their preservation. Encouraging the investment of lands and cultivation of crops to meet the population's need for vegetables and other crops. The findings of this study will help decision-makers develop future urbanisation policies, and it is worthwhile to investigate them further. The prediction model will demonstrate whether built-up areas will continue to grow or not and whether the average agricultural areas will continue to shrink based on regression analysis. Planning effective urban environmental management can benefit from this type of forecast of the LULC picture in the future

COMPARISON OF THREE LABORATORY AND ONE REGRESSION KRIGING METHOD FOR QUANTITATIVE AND QUALITATIVE ASSESSMENT OF SOIL SALINITY IN THE HARRAN PLAIN, SE TURKEY

The Harran Plain occurring in southeastern Turkey, has faced salinity problems since the beginning of irrigated agriculture. Soil salinity is generally most accurately determined from a soil saturation paste (SP) extract. In this study three laboratory (SP, 1:1 and 1:2.5 soil to water ratios) and one kriging technique have been used for the assessment of soil salinity. A total of randomly selected 210 locations, 60 in data set I and 150 in data set II were sampled in 2009 and 2010, respectively, and analyzed for soil electrical conductivity (ECe dS m(-1)), sodium adsorption ratio (SAR) and the soluble cations (Ca2+, Mg (2+), Na+ and K+). Regression analysis was used for quantitative assessments and a classification approach used for qualitative evaluation of salinity. The kriging of residuals and the values from regressions between 1) soil EC(e)s obtained from different soil and water ratios (auxilary variables) and 2) soil salinity variables obtained from saturation paste (primary variables) were combined under regression kriging with the goal of estimating soil salinity parameters. Despite significant correlations among different methods, the results of paired t test showed that averages of soil salinity variables measured with different methods were mostly statistically different (P=0.01). The 1:1 soil water ratio produced the closest results to SP, especially after classification of soils into different salinity groups which provided regression R-2 values up to 0.99. Using a validation with independent samples per cent classification accuracy and kappa statistics of 91 %, 0.72 (p=0.001) were obtained. Kriging combined with regression under regression kriging improved the estimations of K+, Mg2+ and ECe slightly but did not show any improvement over different soil to water ratios for the estimation of SAR, Na+ and Ca2+

Probability mapping of saline and sodic soils in the Harran plain using a non-linear kriging technique

In the Harran Plain, southeastern Turkey, soil salinisation causes land degradation threatening the sustainability of agricultural production. According to a recent survey, approximately 18000 ha area has been affected by soil salinity and sodicity at various levels. Determining the distribution of saline and sodic soils in the study area is the first step for effective management of these soils. Over 200 soil samples have been randomly selected across the plain and analyzed for selected soil salinity and sodicity variables in soil salinity laboratory. Indicator kriging (IK), a non-linear interpolation technique, was used to map the probability levels of occurrence of saline and sodic soils across the plain. The results of IK showed the probability distributions of risky areas under different types of soil salinity classes; nonsaline, saline, saline – sodic and sodic

Boron fertilization of Mediterranean aridisols improves lucerne (Medicago sativa L.) yields and quality

Wetlands are an important component of the terrestrial ecosystem, and play a crucial role in sequestering carbon. However, to date, there is little information about the land-use and nitrogen-fertilization effects on temperature sensitivity of soil respiration in wetland. In this investigation, effects of land use and nitrogen fertilization on temperature sensitivity of soil respiration (Q10) in a freshwater marsh of northeast China were studied. The results showed that change of land use significantly affected Q10-value, which followed the order: Intact Deyeuxia angustifolia wetland soil upland forest soil abandoned cultivated soil cultivated soil. Our data confirmed that soil temperature and moisture were important factors affecting Q10-values. Besides temperature and soil moisture, availability of C and N and microbial activity in soil were important factors affecting Q10-values. Nitrogen fertilization resulted in an increase in Q10-value not only in the intact wetland, but also in the cultivated soil. Although availability of N could stimulate temperature sensitivity of soil respiration, high nitrogen fertilization (i.e., 240 kg N ha-1 in this study) inhibited temperature sensitivity. Further studies are indicated as a means of answering these questions and providing additional information on the effects of nitrogen fertilization on Q10-value