Assessments of Soil physical properties and estimation of their associated variability are essential for making site-specific decisions on soil and crop management This study examined the spatial variability of soil hydro-physical properties and variance structure at Sector F1 of the Jibia Irrigation project Katsina State, Nigeria. Grid sampling technique was used to obtain one hundred and forty-four (144) soil samples from 206 ha of land using Google earth. The grids were drawn using Google earth software at intervals of 150 m x 150 m. Surface soil samples (0 - 20 cm) were collected at grid intersection points. The collected soil samples were air-dried and passed through a 2mm sieve, and analyzed using standard laboratory procedures for physical parameters. The ArcGIS software package 10.3 was used to model the variance structure of Sand, Silt, Clay, Bulk density, Particle density, Percent total porosity and Organic Matter (OM). Results obtained revealed that the coefficient of variation (CV) ranged from 5.724% in particle density to 109% in clay. The Semivariogram showed that the range of spatial dependence varied from 0.342m for (Dry mean weight diameter) to 9.3m (Organic matter) for all measured soil properties. High Spatial dependency ratios were observed for Bulk density, Sand, Silt and clay contents. Particle density exhibited moderate spatial dependency (Nugget to sill ratio 0.25 – 0.75%). Wet Mean weight diameter and organic matter content have a weak spatial dependency. The results indicated that sandy textured soils dominated the greater part of the study area with low to moderate organic matter content. The soils being sandy-dominated has a high infiltration rate and low ability to retain moisture and nutrients were observed as the major characteristics of the soil of the study area.

Basin-based water management strategy is one of the necessary instruments for the protection and sustainable use of water resources against climate change. In this paper, the monthly precipitation distributions of the 25 major basins in Türkiye were produced, and amounts and volumes were computed and analyzed. Only annual modeling and assessments of precipitation may hide months with precipitation shortages. Empirical Bayesian Kriging (EBK), Ordinary Kriging (OK), and Inverse Distance Weighting (IDW) were implemented in interpolation. EBK outperformed in all months and calculations were based on the EBK. The month with the highest precipitation potential in Türkiye is December (77.9 mm, 60.77 billion m3), and the month with the lowest precipitation potential is August (13.8 mm, 10.76 billion m3). In the basins, the monthly precipitation amounts range between 2.7 mm and 185.2 mm, and the volumes range between 0.02 billion m3 and 13.24 billion m3. The basins with the highest precipitation depth were determined as the East Black Sea, Antalya, Asi, and Ceyhan, and the lowest as the Small Menderes, Konya, and Tigris-Euphrates in different months. The monthly precipitation patterns and potentials of the basins vary widely. In May, June, July, August, and September, when water, particularly agricultural irrigation, is required the most, the 20 basins, except for the 5 located in Northern Türkiye precipitation shortage was determined.