Given that Qazvin Province located in the seventh drought place in the country and need to manage vast water resources. Water storage estimation methods have developed over the years and observation of changes in the gravitational field by satellite GRACE is one of these methods. This satellite produces a series of water storage changes data with spatial resolution of 1 ° on a regional scale. This study aimed to evaluate data from GRACE satellites in Qazvin province to find a comprehensive solution for quick and easy access to the water resources. To validate the GRACE satellite data, land surface model data (GLDAS) and wells data in the region were used. The results show that the GRACE satellites as a Gravity satellite just produce to estimate changes in Earth's water supply, give a good estimate of the changes in the ground water storage and groundwater level changes. Statistical analysis showed that RMSE =5.54, MAE = 4.16 and MBE = 1.5 the seasonal scale in millimetre between groundwater level data from the GRACE satellites and observation wells, and RMSE =2.92, MAE = 4.24 and MBE =0.184month scale in centimetre between the data changes in land water storage from GRACE satellite and GLDAS model. Also, the correlation between changes in water storage data from the GRACE satellite and GLDAS model and groundwater level changes from GRACE satellite and observational data is significant at the 99% probability level. The results showed that GRACE satellite shows terrestrial water storage changes better than GLDAS model.

The drop in water level in the aquifers of Kermanshah province has been so severe that it has reached about 10 meters in some places. The purpose of this study is to evaluate GRACE satellite data to estimate the groundwater storage of Ravansar aquifer in Kermanshah province. Therefore, in this study, while examining the water level of Ravansar aquifer observation wells and also the spatial zoning of these changes, the current situation of the region was evaluated using Kriging method in GIS software. Then, in order to evaluate the GRACE satellite data, the JPL, GFS, CSR, and CRI algorithms were coded in Google Earth Engine cloud computing environment, and then the monthly and annual changes of liquid water Equivalent (LWE) were calculated. Also, the amount of Soil Moisture (SM) was estimated from the GLDAS hydrological model and by subtracting the amount of soil moisture from the estimated values of GRACE , the amount of changes in groundwater storage compared to its observational values was obtained. This study showed that not only can GRACE data be used to estimate the rate of changes in groundwater storage in aquifers, but also the data are of acceptable accuracy. Comparison of the results of different algorithms showed that the JP algorithm with a correlation coefficient of 0.73 has the highest correlation with observational data. According to the JPL , the values of changes in groundwater storage estimated from GRACE compared to the observed values show a decrease in groundwater storage of -1.8 cm.

Determining groundwater storage changes, especially in arid and semiarid areas, is a vital issue for groundwater management and planning. GRACE satellite produces changes in water storage with 1 degree spatial resolution using Earth's gravity field changes. In this study, it is tried to evaluate monthly groundwater storage changes between August 2002 and June 2016 in two pixels of one square degree of Khorasan Razavi province, which cover the whole area or parts of 6 aquifers using data from four GRACE satellite information processing centers named CENS, CSR, GFZ and JPL. Utilizing amount of Terrestrial Water Storage (TWS) obtained from GRACE satellite data, with data of soil moisture, snow water equivalent and canopy water storage derived from the GLDAS model which are presented with 1 degree spatial resolution on a monthly basis lead to estimates of monthly groundwater level changes. An estimation of monthly changes in groundwater level of the GLDAS model was obtained at a 25 degrees resolution in order to compare with the results of the GRACE satellite data. Observational data containing monthly groundwater level changes from the piezometric wells of the study area were used to validate the results. The results show that data of GRACE (CENS) with (RMSE = 14.35 and MAE = 12.645) are the weakest estimation of groundwater level changes. While the GRACE (JPL) data with RMSE = 5.708 and MAE = 5.038 shows the best estimation. It should be noted that the GLDAS model data with a resolution of 0.25 degree with an RMSE of 2.350 cm and a MAE of 1.826 cm shows a more appropriate estimate than the GRACE data types. GRACE data (CSR) showed the most favorable prediction of the trend of monthly changes in groundwater level by presenting a trend of -0.089 cm / month.

The GRACE mission has substantiated the Low–Low Satellite-to-Satellite Tracking (LL-SST) concept. The LL-SST configuration can be combined with the previously realized high–low SST concept in the CHAMP mission to provide a much higher accuracy. The line of sight (LOS) acceleration difference between the GRACE satellite pair is the most frequently used observable for mapping the global gravity field of the Earth in terms of spherical harmonic coefficients. The following relationship is valid for each evaluation point: (1) The GRACE ranging system provides inter-satellite range and its first time derivative,, as the LL-SST observations and the GPS receivers mounted on the GRACE satellites provide the position vectors as the HL-SST mode observations. The inter-satellite range acceleration,, and are obtained by numerical differentiation of and, respectively. In the absence of non-gravitational forces, the left-hand side of Eq. (1) can be considered as the LOS gravitational acceleration differences, (2) A sequence of observations with evaluation points sets up a system with linear equations. In this paper, the corresponding linear system of equations has been set up for spherical harmonic up to degree and order 120. The total number of unknowns,, is (3) Such a linear equation system can be solved with iterative solvers or direct solvers. However, the runtime of direct methods or that of iterative solvers without a suitable preconditioner increases tremendously. This is the reason why we need a more sophisticated method to solve the linear system of problems with a large number of unknowns. Multiplicative variant of the Schwarsz alternating algorithm is a domain decomposition method, which allows it to split the normal matrix of the system into several smaller overlaped submatrices. In each iteration step the multiplicative variant of the Schwarz alternating algorithm solves linear systems with the matrices obtained from the splitting successively. It reduces both runtime and memory requirements drastically. An MSAA example with two submatrices is shown in Fig. 1 Figure 1. MSAA example with two submatrices. This method dates back to H. A. Achwarsz’ work, published in 1980, and has been investigated by many authors since then. In this paper we propose the Multiplicative Schwarz Alternating Algorithm (MSAA) for solving the large linear system of gravity field recovery. The proposed algorithm has been applied in a close-loop simulation to the International Association of Geodesy (IAG)-simulated data of the GRACE mission. The achieved results indicate the validity and efficiency of the proposed algorithm in solving the linear system of equations from accuracy and runtime points of view.

Global database and satellite products with high spatial and time-lapse power, can be seen as a suitable alternative source for conducting studies of water balance components in statistically deficient areas and areas with no uniform distribution of stations. Use of this data provided that it has sufficient accuracy, for Iran, which many of its parts, especially desert and mountainous areas, due to the low density of stations, the short statistical period of new stations always faces problems of accessing local and time information in the region. They will be, of great importance it is. The main goal of the research is to assess the global database and satellite products to estimate real rainfall, Evapotranspiration, and changes in water storage in the Tashk-Bakhtegan basin. Used GLDAS, PERSIANN - CDR, CHIRPS, NCEP database to assess the rainfall according to our objectives. For real Evapotranspiration, the real amounts of evaporation and absorption were first extracted based on the Balance Torrent White equation, and the results were evaluated by the GLDAS database, GLEAM. The GRACE satellite was used to estimate the changes in the region's water reserves and to assess it the GLDAS satellite was used to extract annual changes in groundwater. Results obtained showed that the PERSIANN - CDR database performed best and consistent with its observational data across all statistical indicators before and after the Bias correction. GLEAM also had the best statistical performance in estimating Evapotranspiration before and after correction with Balance Torrent White Equation data. Comparison of the observation levels of underground water with data extracted from GRACE and GLDAS satellites indicates the existence of a similar trend, and, based on the power of GRACE's low locality segregation and the low area studied, the results for groundwater changes and Ground water is acceptable. The results of the present study show data from the PERSIANN- CDR satellite for rain, GLEAM model for real evaporation and absorption and GRACE satellite for estimating ground water changes as a convenient tool for making early, quick and low - cost estimates on Water Balance Components It will be used.

The main objective of the paper is determination of the geoidal potential, using satellite altimetry, Jason-2, and GRACE data. This purpose has been carried out according to the following algorithms Preparation of 80 cycles, about 27 month, of Jason-2 altimeter raw data, 2. Applying all necessary corrections such as: tidal, atmospheric and instrumental corrections, on the raw data to determinate corrected sea surface heights (COSSH); 3. Computing monthly Earth's gravity potential at the mean sea surface points, using GRACE monthly spherical harmonic coefficients 4. Removing parts of data related to the world greatest Lakes, especially the Caspian; and 5. Averaging of remaining data to determinate the geoidal potential. The results indicated that the average of geoidal potential, from July 2008 to September 2010 is about has been, where the highest monthly changes related to semi-annual variations is about.

The aim of this research is to predict fluctuations in the equivalent thickness of groundwater using GRACE satellite data and modeling it using artificial intelligence hybrid models. The study area of this research is the basin area of Lake Urmia located in the northwest of Iran. For this purpose, 180 GRACE satellite data between April 2002 and March 2017 were used. The output of GRACE satellites includes 6 pixels located on the selected watershed, of which 2 points that overlapped the most with the watershed area were selected for modeling with artificial intelligence tools. The GA-ANN, ICA-ANN and PSO-ANN hybrid models were used for this purpose. The results showed that the output of the ICA-ANN model had the best fit with the observation data with a correlation coefficient equal to 0.915 and 0.942 in the two selected pixels 2 and 5 in the test phase, and the results of this model had the best and closest distribution of points. Considering the importance of knowing the changes in the equivalent thickness of groundwater as one of the most important parameters of the water budget, the artificial intelligence models used in this research can be recommended, especially for areas without basic statistics or in situations where it is not possible to use mathematical models. Without the need for complex relationships and equations to investigate the effect of surface and groundwater interaction and only based on satellite data, the equivalent thickness of groundwater can be predicted in the studied plain in dry and wet periods with great accuracy.

The GRACE mission has provided scientific community Time-variable gravity field solutions with high precision and on a global scale. The GRACE mission was launched on March 2003. This mission consists of two satellites that pursue each other in their orbit. Distance between two satellites in orbit is measured continuously to an accuracy of better than 1 micron using KBR system placed in satellites. As the satellite fly in the gravity field، this distance changes and by monitoring those changes the gravity field can be determined. To reduce non-gravitational accelerations، each satellite has an on-board accelerometer to measure these accelerations (Wahr and Schubert، 2007). Providing profiles of the atmosphere using GPS measurements for gaining knowledge about the atmosphere is another goal of this mission. One of the products of this mission is GRACE LEVEL-2. This product consists of monthly spherical harmonic coefficients up to degree 120. One application of these coefficients is to determine time-variable gravity field. The time-variable gravity field is then used to solve for the time-variable-mass field (Wahr and schubert، 2007). A mathematical model for determining the surface density (mass) variations using spherical harmonic coefficients is presented by Wahr et al. (1998). This mathematical model is as follows: Where، ،، ،، ،، are surface density variations، mean earth density، mean earth radius، Love number of degree، GRACE potential changes، fully normalized Legendre functions، degree and order respectively. Spherical harmonic coefficients from the GRACE are noisy which increase rapidly with increasing degree of geopotential coefficients. In addition، monthly surface mass variations map shows the presence of long، linear features، commonly referred as stripes (Swenson and Wahr، 2006). Hence، in different methods of filtering it is tried to solve both problems. Filtering of the GRACE gravity solutions has been studied extensively. For some of the recent contributions we refer to Wahr et al. (1998)، Chen et al. (2005)، Swenson and Wahr (2006)، Kusche (2007)، Sasgen et al. (2006)، ، Swensonand Wahr (2011)، Save et. al. (2012). In this paper، for filtering the GRACE gravity solutions، we propose a new way of determining the surface mass change formula under the assumptions considered in Wahr et al. (1998) by means of Singular Value Expansion of the Newton’s Integral equation as an Inverse Problem. Let be the potential change caused by just Earth''s surface mass change، then: or in operator form: Where is an integral operator with kernel. Series expansion of the kernel based on Associated Legendre functions is as follows: Now، by means of singular value expansion، singular system for this operator is as follows: where and، ، are singular values، right singular vectors، left singular vectors، respectively. In terms of singular value expansion، the surface density variation can be written as follows: where s are filter coefficients that are determined by regularization methods. In this paper، filter coefficients are determined from regularization methods، such as Truncated SVE، Damped SVE and the Standard and Generalized Tikhonov methods in Sobolev subspace. The numerical results show a good performance of the method “Generalized Tikhonov in Sobolev subspace”، which effectively reduces the noise and the stripes.

Determining groundwater changes in Iran, which is located in arid and semi-arid regions, is of particular importance. In this regard, Kermanshah province with 950,000 hectares of agricultural land and gardens is one of the agricultural hubs of the country and the water level in the aquifers of the province, especially in the eastern part of the province is more severe. In this study, by examining the water level of the observational wells of Mianrahan aquifer in Jamishan basin and spatial zoning of these changes using Kriging method in GIS software, the current situation of the region has been investigated. In order to evaluate GRACE satellite data with JPL, GFS, CSR, CRI data centers, coding in Google Earth Engine cloud computing environment has been used. Monthly and annual changes of liquid water equivalent (LWE) were calculated. Comparing the results of different data centers show that JPL data center with coefficient of R = 0.66 has the highest correlation with observational data. The amount of soil moisture, snow water equivalent and plant canopy water was extracted from the GLDAS model and subtracted from the amount of TWS extracted from the GRACE satellite and was compared with the observed values, which shows that the trend of decreasing groundwater level is equal to -2.26 cm. Calculations are made on the scale of one square degree and units are expressed in centimeters.