JWSS - Journal of Water and Soil Science

To continue or develop the exploitation of underground water for different different uses and purposes, as well as building any water structure, set of quantitative features of aquifers can be detected. To achieve this goal, quantitative monitoring of groundwater level is only possible. Accordingly, this study compared the impact of both the concept of marginal entropy and ordinary kriging for groundwater level monitoring network design in the case Gotvand-Aghili Plain, Khuzestan province. It is important to note that a key aspect in groundwater level monitoring of the quantity measured was the variability or uncertainty in it. This created a considerable confidence to monitor and ultimately achieve favorable conditions in the future. In this study, the variability of the groundwater level was considered to evaluate the combined effects of marginal entropy and ordinary kriging. In order to determine the suitable areas for further monitoring or thinning as well as the compatibility of these two methods, the monitor network design was designed. The map classified according to the marginal entropy method, in a range between 0.07 to 5.26 of the marginal entropy change, areas with the higher rates of 2.13 in terms of density; this indicated the need for more observation wells. Ordinary Kriging method also changed the range of values; they also represented areas that needed monitoring more than 13.16. Comparison of the results obtained by the two methods showed that the marginal entropy of the kriging method with less uncertainty and by using it, there was less the need to be monitored and classified. Comparison of the two methods by the zoning map showed that fewer errors were taken to the marginal entropy method and it could be recommended for the groundwater level monitoring network design. The network was also based on the Cross validation estimation error evaluated. These tests and additional analysis were employed in this study to determine the suitable areas for the higher density of wells and the need for thinning areas. The results further confirmed the proper performance of the methods employed, as well as the superiority of the marginal entropy in the design of a small groundwater monitoring network.

Evaporation is one of the important components in water body’s management, leading to changes in the water level and water balance. Also, its accurate estimation is faced with certain difficulties and complexities. Because of the limitations of physical and empirical methods based on the meteorological data, remote sensing technology can be widely used for evaporation calculation due to its capabilities for spatial data estimation and minimization of the meteorological data application. Many models have been developed to estimate evapotranspiration using remote sensing technology. Regarding the use of these algorithms for estimating evaporation from water surface, a few studies have been done; however, there is yet no comparison between them to estimate evaporation from the water surface. For this purpose, in this study, the output from two models estimating spatially distributed evaporation of water surfaces from remotely sensed imagery is compared. In order to implement these models, Terra/MODIS Images for four months including June, July, August and September in of 2006, 2007, 2008 and 2009 were prepared. Comparisons were made using pan data from Urmia synoptic station. In general, there was a reasonable agreement between the evaporation outputs from both models versus a pan data observation. The statistical analysis also showed that the SEBS algorithm (by applying the salinity factor), despite being simple in its implementation, has higher accuracy than the SEBAL algorithm.

Drought is one of the most complex natural disasters due to its slow onset and long-term impact. Today, the use of remote sensing techniques and satellite imagery has been considered a useful tool for monitoring agricultural drought. The objective of the present study was to evaluate spatial and temporal monitoring of agricultural drought in the lake Urmia catchment area with the ETDI drought index which is calculated from Nova satellite images based on actual evapotranspiration from the SEBS algorithm and compared with the ground index SPI. For this purpose, 248 AVHRR sensor images and NOAA satellites during the statistical period of 1998-2000 and 17 meteorological stations with a statistical period of 30 years were used to calculate the indicators. To determine agricultural lands, six thousand points were marked for different uses and their actual evapotranspiration was calculated using the SEBS algorithm. The results showed that with the onset of the drought period in 1998, the ETDI index indicated 9.4% in weak drought conditions in May and 90.6% in normal conditions. Over time, in June of 1998, the situation was different with 95% in a weak drought situation and 5% in a normal situation for the city of Tabriz. In July, the entire catchment area experiences a slight drought. Then, in August, 84% of the basin is in normal condition and 16% in Tabriz and Urmia are declared weak drought. It was also founded that the ETDI drought index due to the combination of visible and infrared bands and its combination with terrestrial data has a physical meaning and has high certainty and predicts drought faster and more accurately.