Evapotranspiration is an important component in many hydrological, ecological and agricultural studies. There are many available direct and indirect methods to determine the evapotranspiration rate. In this study, alternative model based on multilayer Artificial Neural Network (ANN) using the backpropagation algorithm was proposed to estimate evapotranspiration as referred to pan evaporation. The meteorological data used in this study were obtained from Al-Zahra and Al-Zawia stations which located on the coastal area of western Libya lie. The input data were consisted of mean temperature, mean relative humidity and mean of actual sunshine hours of consecutive years (1995, 1996, 1997 and 1999). The performance of the ANN model was evaluated against a set of data that never seen by the model during the training phase. The evaluation of ANN model was also performed against Blaney and Criddle, Radiation and modified Penman methods. The results showed that ANN forecasts were superior to the ones obtained by Blaney and Criddle and Radiation methods. Due to its little input data, ANN is considered to be more efficient as compared with the modified Penman method. However, this application of ANN as a fitting tool should be useful in evapotranspiration modeling. Keywords: Evapotranspiration Pan evaporation, Artificial neural networks, Backpropagation algorithm.
Ahmed Ibrahim Ekhmaj(1-2012)

Soil databases are very important for assessing ecosystem services at different administrative levels (e.g., state, region etc.). Soil databases provide information about numerous soil properties, including soil inorganic carbon (SIC), which is a naturally occurring liming material that regulates soil pH and performs other key functions related to all four recognized ecosystem services (e.g., provisioning, regulating, cultural and supporting services). However, the ecosystem services value, or “true value,” of SIC is not recognized in the current land market. In this case, a negative externality arises because SIC with a positive value has zero market price, resulting in the market failure and the inefficient use of land. One potential method to assess the value of SIC is by determining its replacement cost based on the price of commercial limestone that would be required to amend soil. The objective of this study is to assess SIC replacement cost value in the contiguous United States (U.S.) by depth (0–20, 20–100, 100–200 cm) and considering different spatial aggregation levels (i.e., state, region, land resource region (LRR) using the State Soil Geographic (STATSGO) soil database. A replacement cost value of SIC was determined based on an average price of limestone in 2014 ($10.42 per U.S. ton). Within the contiguous U.S., the total replacement cost value of SIC in the upper two meters of soil is between $2.16T (i.e., 2.16 trillion U.S. dollars, where T = trillion = 1012) and $8.97T. States with the highest midpoint total value of SIC were: (1) Texas ($1.84T), (2) New Mexico ($355B, that is, 355 billion U.S. dollars, where B = billion = 109) and (3) Montana ($325B). When normalized by area, the states with the highest midpoint SIC values were: (1) Texas ($2.78 m−2), (2) Utah ($1.72 m−2) and (3) Minnesota ($1.35 m−2). The highest ranked regions for total SIC value were: (1) South Central ($1.95T), (2) West ($1.23T) and (3) Northern Plains ($1.01T), while the highest ranked regions based on area-normalized SIC value were: (1) South Central ($1.80 m−2), (2) Midwest ($0.82 m−2) and (3) West ($0.63 m−2). For land resource regions (LRR), the rankings were: (1) Western Range and Irrigated Region ($1.10T), (2) Central Great Plains Winter Wheat and Range Region ($926B) and (3) Central Feed Grains and Livestock Region ($635B) based on total SIC value, while the LRR rankings based on area-normalized SIC value were: (1) Southwest Plateaus and Plains Range and Cotton Region ($3.33 m−2), (2) Southwestern Prairies Cotton and Forage Region ($2.83 m−2) and (3) Central Great Plains Winter Wheat and Range Region ($1.59 m−2). Most of the SIC is located within the 100–200 cm depth interval with a midpoint replacement cost value of $2.49T and an area-normalized value of $0.34 m−2. Results from this study provide a link between science-based estimates (e.g., soil order) of SIC replacement costs within the administrative boundaries (e.g., state, region etc.). arabic 19 English 114
Garth Groshans, Elena Mikhailova, Christopher Post, Mark Schlautman, Hamdi Zurqani, Lisha Zhang(12-2018)

Sodicity and salinity can adversely affect soil structure and are common constraints to plant growth in arid regions. Current remote sensing techniques cannot distinguish between the various classes of salt-affected soils. Field and laboratory measurements of salt-affected soils are time-consuming and expensive. Mapping of the salt-affected soils can be used in soil conservation planning to identify regions with different degrees of limitations. There is a need to use existing field and laboratory measurements to create maps of classes of salt-affected soils. The objectives of this study are to classify salt-affected soils, use existing field data to interpolate and validate geospatial predictions of the classes of salt-affected soils using Geographic Information Systems (GIS), and create maps showing the different classes and distribution of salt-affected soils. The classification framework for salt-affected soils is based on electrical conductivity (ECe), soil pH and the sodium adsorption ratio (SAR), and provides four degrees of limitations to salt-affected soils: slight (normal soils), moderate (saline soils), severe (sodic soils), and extreme (saline-sodic soils). Spatial interpolation of the field data from northwestern Libya was verified by cross-validation, and maps of the salt-affected soils in the region were created. The majority of soils in this region of Libya are normal (slight degree of limitation). Twenty percent of the topsoil is saline-sodic (extreme degree of limitation). Land use recommendations and rehabilitation strategies can be developed from such maps of salt-affected soil classes. The methodology followed in this study can be applied to other arid regions around the world, particularly in developing countries where budgetary constraints limit detailed field and laboratory measurements of sodicity and salinity. arabic 11 English 70
Hamdi Zurqani, Elena Mikhailova, Christopher Post, Mark Schlautman, Julia Sharp(2-2018)