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Investigating the Effects of Sustainability of Climate Change on the Agriculture Water Consumption in the Zayandeh-Rud River Basin
M. J. Zareian, S. S. Eslamian, H. R. Safavi,
Volume 20, Issue 75 (5-2016)
Abstract

This study investigated the effects of climate change on the evapotranspiration amount and water balance in the Zayandeh-Rud river basin. Two important weather stations; Isfahan and Chelgerd stations, located in the East and West of the basin respectively, were selected for investigation in this study. The combination of 15 GCM models were created based on the weighting method and three patterns of climate change including the ideal, medium and critical were defined. Using the proposed patterns, the effects of climate change on temperature and evapotranspiration in Isfahan station and precipitation in Chelgerd station were estimated under the A2 and B1 emissions scenarios. Two indices were considered to determine the sustainability of agricultural water consumption in the study area. Ratio of evapotranspiration in the East part of the basin to precipitation in the West part was defined as EPR index (Evapotranspiration-Precipitation Ratio), and the ratio of maximum agricultural water deficit to the amount of agriculture water need, was considered as maximum deficit index (MD). Results showed that the annual temperature would increase between 0.63-1.13°C in the eastern part of the basin. The west precipitation in the basin would reduce between 6.5-30% in the ideal to critical patterns. Summer season, showed the most amount of increase in the temperature, and winter season, showed the most amount of decrease in precipitation. The A2 emission scenario showed more temperature increase and more precipitation decrease in comparison with the B1 emission scenario and also indicated that the potential evapotranspiration would increase by 3.1 to 4.8% in the basin. The EPR index will increase between 13-52% and MD index will increase between 9-35% in Zayandeh-Rud river basin under different climate change patterns. The results revealed the imbalance between agricultural water use in eastern part and the precipitation in the western part of the basin. In other words, in these conditions, appropriate management strategies and planning should be implemented to ensure the sustainability of water resources in Zayandeh-Rud River Basin.


Using the Principal Component Analysis Approach for Weighting Statistical, Climatic and Geographical Attributes of the Maximum 24-hour Rainfall and Spatial Clustering Analysis (A Case Study: Urmia Lake Basin)
Z. Dehghan, S. S. Eslamian, R. Modarres,
Volume 22, Issue 4 (3-2019)
Abstract
Regionalization is one of the useful tools for carrying out effective analyses in regions lacking data or with having only incomplete data. One of the regionalization methods widely used in the hydrological studies is the clustering approach. Moreover, another effective factor on clustering is the degree of importance and participation level for each of these attributes. In this study, it was tried to use a broad range of attributes to compare their performance in regionalization. Then, according to the importance and role of each attribute in regionalization, the appropriate weight for each of the attributes in each category was determined using the principal component analysis (PCA) method, and the effect of this weighting in forming the homogenous regions was investigated by the Ward's clustering method. In this regard, the maximum 24-hour rainfall data of 63 meteorological stations located in Urmia Lake Basin (ULB) was used in this study during a time period of 30 years (1979-2008). Furthermore, seven categories of attributes were defined in order to regionalize the rainfall. The results showed that by considering different attributes and combining them with each other, a different clustering is obtained in each category in terms of the number of clusters and stations. Among seven categories of attributes, it was found that the geographical and climatic-geographical categories of attributes showed a more appropriate clustering over the ULB. Additionally, the weighting of attributes could have more effect on improving homogeneity and forming the independent clusters in most cases in terms of the scattering of station and how to locate over the basin.

Evaluation of Spatial Variations of Soil Infiltration and its Models Parameters Using Geostatistics (A case study: Mansour Abad Plain)
R. Azadikhah, M. Sedghiasl, E. Adhami, H. R. Owliaie, A. Karami, Sh. Saadipour,
Volume 23, Issue 2 (9-2019)
Abstract
The aim of this study was to evaluate the spatial distribution of soil infiltration using geostatistics methods in a regional scale on 400 hectares of Mansour Abad Plain, in Larestan region, Fars Province. Sampling and parameters measurement were done for 78 points in a regular grid with a distance of 100*100 meters; for these variables, the best variogram model between linear, exponential, Gaussian and spherical models with the highest R2 and the lowest error was determined using GS+ and ArcGIS software. In this study, soil infiltration (cm/min) using the double ring method and some other soil properties including soil electrical conductivity (dS/m), pH, saturation percentage (%SP), particle size percentage (sand, silt and clay), and calcium (meq/lit), magnesium (meq/lit), sodium (meq/lit) were measured and determined. The spatial distribution of Kostiakov and Philip models parameters and theri zoning were determined using the geostatistic method. The results showed that, among different soil properties, the final infiltration rate had a high degree of variability in the study area, and the decision was based on the usual averaging methods, which could have a lot of error. Among applied infiltration models, Kostiakov model and Philip model were the best empirical and physical infiltratin models, respectively, in the studied area. The best semivariogram model for the steady state infiltration rate was Philip model, with the coeficients of S and A, and a coefficient of Kostiakove model was gaussian; for the b coefficient, Kostiakove model was exponential. Spatial structure of the final infiltration rate, a and b coefficients of Kostiakove model, and S and A coefficients of the Philip model, was strong. The best interpolation method for the final infiltration rate was cokriging with the cofactor of silt percentage, for the S coefficient of Philip model was inverse distance weighting (IDW); for a and b coefficients of Kostiakove model, kriging and IDW were suitable, respectively.

Application of a Self-Organizing Map for Clustering the Groundwater Quality in Kerman Province and Assessment its Suitability for Drinking and Irrigation Purposes
F. Soroush, A. Seifi,
Volume 23, Issue 2 (9-2019)
Abstract
Evaluation of groundwater hydro chemical characteristics is necessary for planning and water resources management in terms of quality. In the present study, a self-organizing map (SOM) clustering technique was used to recognize the homogeneous clusters of hydro chemical parameters in water resources (including well, spring and qanat) of Kerman province; then, the quality classification of groundwater samples was investigated for drinking and irrigation uses by employing SOM clusters. Patterns of water quality parameters were visualized by SOM planes, and similar patterns were observed for those parameters that were correlated with each other, indicating a same source. Based on the SOM results, the 729-groundwater samples in the study area were grouped into 4 clusters, such that the clusters 1, 2, 3, and 4 contained 73%, 6.2%, 6.7%, and 14.1% of groundwater samples, respectively. The increase order of electrical conductivity parameter in the clusters was as 1, 4, 3 and 2. The results of water quality index based on the entropy weighting (EWQI) showed that all of the samples with excellent and good quality (36.3% of samples) for drinking belonged to the cluster 1. According to the Wilcox diagram, 435-groundwater samples (81.7%) in the cluster 1 had the permitted quality for irrigation activities, and the other 285-groundwater samples were placed in all four clusters, indicating the unsuitable quality for irrigation. The Piper diagram also revealed that the dominant hydro chemical faces of cluster 1 were Na-Cl, Mixed Ca-Mg-Cl and Ca-HCO3, whereas the clusters 2, 3, and 4 had the Na-Cl face. This study, therefore, shows that the SOM approach can be successfully used to classify and characterize the groundwater in terms of hydrochemistry and water quality for drinking and irrigation purposes on a provincial scale.

Prioritization and Assessment of Groundwater Resources Map in Isfahan Province
M. Moradizadeh, K. Shirani,
Volume 23, Issue 4 (2-2020)
Abstract
Water resources management depends on the precise assessment of water storage and access in each region, as well as environmental interactions of these resources. The man objective of this study was to delineate the potential zones of groundwater storage using FAHP. Mapping and assessment of it required maps of geomorphology, drainage, density, lineament density, slope and vegetation, which were initially prepared as the input layers in FAHP; the appropriate weights were attributed to them based on FAHP. Potential zones of ground water were classified into five classes of poor, average, good, very good and excellent. The number and density of available wells and springs in the study area dealt with the potential of the region for groundwater storage. So, ROC was used to assess the validation of results, considering spring points as signs of water resources. According to the results, classes of very good, good, average, weak, and very weak were ranked as the first to the last in terms of privilege order with an area of 37.7, 55, 40, 107, and 98.4 square kilometers, respectively.

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