Artificial recharge efficiency assessment by soil water balance and modelling approaches in a multi-layered vadose zone in a dry region

Pakparvar, M; Hashemi, Hossein; Rezaei, Meisam; Cornelis, Wim; Nekooeian, Gholamali; Kowsar, Sayyed Ahang

doi:10.1080/02626667.2018.1481962

Cited by 13 publications

(5 citation statements)

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“…It provides a potentially wide range of additional opportunities for MAR such as transferring water from ephemeral rivers into aquifers during storm events and at times when storage in surface water reservoirs exceeds capacity (e.g., end of spring and early summer) or when reservoir storage is released because of flood control measures (e.g., during and after heavy rainfalls). Flooding has proven to be beneficial in arid regions with wet seasons that are not far from mountain ranges (Hashemi et al, ; Pakparvar et al, ). California Department of Water Resources (DWR) has recently started a flood‐MAR initiative, focusing on the use of flood water on aquifer recharge and sustainable use of water resources (California DWR, ).…”

Section: Introductionmentioning

confidence: 99%

An Integrated Approach Toward Sustainability via Groundwater Banking in the Southern Central Valley, California

Ghasemizade

Asante

Petersen

et al. 2019

Water Resources Research

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Intensive groundwater withdrawals in California have resulted in depletion of streams and aquifers in some regions. Agricultural managed aquifer recharge (Ag‐MAR) initiatives have recently been piloted in California to mitigate the effects of unsustainable groundwater withdrawals. These initiatives rely on capturing wet‐year water and spreading it on large areas of irrigated agricultural lands to enhance recharge to aquifers. While recharge studies typically consider local effects on aquifer storage, few studies have investigated Ag‐MAR benefits and challenges at a regional scale. Here we used the Integrated Water Flow Model, to evaluate how Ag‐MAR projects can affect streamflows, diversions, pumping, and unsaturated zone flows in the southern Central Valley, California. We further tested the sensitivity of three different spatial patterns of Ag‐MAR, each chosen based on different thresholds of soil suitability, on the hydrologic system. This study investigates how the distribution of Ag‐MAR lands benefit the regional groundwater system and other water balance components. The results suggest that Ag‐MAR benefits vary as a function of the location of Ag‐MAR lands. Stream‐aquifer interactions play a crucial factor in determining the ability to increase groundwater storage in overdrafted basins. The results also indicate that Ag‐MAR projects conducted during the November–April recharge season have implications for water rights outside of the Ag‐MAR season. If not properly monitored, Ag‐MAR can cause a rise of groundwater table into the root zone, negatively impacting sensitive crops. Our work also highlights the benefits of using an integrated hydrologic and management model to evaluate Ag‐MAR at a regional scale.

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Section: Introductionmentioning

confidence: 99%

An Integrated Approach Toward Sustainability via Groundwater Banking in the Southern Central Valley, California

Ghasemizade

Asante

Petersen

et al. 2019

Water Resources Research

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“…The population explosion, economic development, and urbanization have increased the pressure on groundwater consumption [44,45], while land use affects the change and distribution of TWS by changing the recharge rates [43]. The elevation and slope degree has a direct influence on runoff, erosion, and the transport of sediments [46][47][48]. Finally, Landsat Tree Cover Continuous Fields (LTCCF) data reflect the distribution (especially evapotranspiration) of water resources at the surface [49].…”

Section: Datamentioning

confidence: 99%

Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods

2021

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High-resolution and continuous hydrological products have tremendous importance for the prediction of water-related trends and enhancing the capability for sustainable water resources management under climate change and human impacts. In this study, we used the random forest (RF) and extreme gradient boosting (XGBoost) methods to downscale groundwater storage (GWS) from 1° (~110 km) to 1 km by downscaling Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data from 1° (~110 km) and 0.25° (~25 km) respectively, to 1 km for China. Three evaluation metrics were employed for the testing dataset for 2004−2016: The R2 ranged from 0.77−0.89 for XGBoost (0.74−0.86 for RF), the correlation coefficient (CC) ranged from 0.88−0.94 for XGBoost (0.88−0.93 for RF) and the root-mean-square error (RMSE) ranged from 0.37−2.3 for XGBoost (0.4−2.53 for RF). The R2 of the XGBoost models for GLDAS was 0.64−0.82 (0.63−0.82 for RF), the CC was 0.80−0.91 (0.80−0.90 for RF) and the RMSE was 0.63−1.75 (0.63−1.77 for RF). The downscaled GWS derived from GRACE and GLDAS were validated using in situ measurements by comparing the time series variations and the downscaled products maintained the accuracy of the original data. The interannual changes within 9 river basins between pre- and post-downscaling were consistent, emphasizing the reliability of the downscaled products. Ultimately, annual downscaled TWS, GLDAS and GWS products were provided from 2004 to 2016, providing a solid data foundation for studying local GWS changes, conducting finer-scale hydrological studies and adapting water resources management and policy formulation to local condition.

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“…The parameters and conditions applied during the simulation process are summarized in Table 2. Contrary to Rahmati et al (2020), who simulated the infiltration process up to 240 h, in this study we limited the simulations to the duration of 24 h, as infiltration measurements rarely last more than 24 h. We also assumed that the water level in the system can be measured with a time interval of 1 min, in line with most experimental devices and protocols (Angulo-Jaramillo et al, 2000Pakparvar et al, 2018;Rezaei et al, 2016Rezaei et al, , 2020. We account for this by rounding up the simulated infiltration time data expressed in minutes to T A B L E 1 Average values of soil hydraulic parameters of van Genuchten (VG) model (van Genuchten, 1980) for water retention curve for examined soil texture classes (Carsel & Parrish, 1988) used as synthetic data, as well as the sorptivity (S) data being obtained from the horizontal infiltration simulation (Rahmati et al, 2020).…”

Section: Synthetic Datamentioning

confidence: 99%

Simplified characteristic time method for accurate estimation of the soil hydraulic parameters from one‐dimensional infiltration experiments

Rahmati

Rezaei

Lassabatère

et al. 2021

Vadose Zone Journal

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Recently, a novel approach with excellent performance based on the concept of the characteristic infiltration time, the characteristic time method (CTM), is proposed to infer soil sorptivity (S) and saturated hydraulic conductivity (K s ) from onedimensional (1D) cumulative infiltration. The current work provides a simplified version of the CTM, called the SCTM, by eliminating the necessity of the iteration method used in CTM and providing a similar accuracy as the original method when estimating S and K s . We used both synthetic and experimental data to evaluate SCTM in comparison with the original CTM, as well as Sharma (SH) and curvefitting methods. In the case of synthetically simulated infiltration experiments, the predicted S and K s values showed an excellent agreement with their theoretical values, with Nash-Sutcliffe (E) values higher than 0.9 and RMSE values of 0.11 cm h 1/2 and 0.35 cm h -1 , respectively. In the case of experimental data, the SCTM showed E values larger than 0.73 and RMSE values of 0.64 cm h 1/2 and 0.35 cm h -1 , respectively. The accuracy and the robustness of SCTM was comparable with the original CTM when applied on synthetic infiltration curves as well as on experimental data. Similar to the original CTM, the simplified approach also does not require the knowledge of the time validity, which is needed when using approaches based on Philip's infiltration theory. The method is applicable to infiltrations with durations from 15 min to 24 h. The supplemental material presents the calculation of S and K s using SCTM in an Excel spreadsheet.

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Artificial recharge efficiency assessment by soil water balance and modelling approaches in a multi-layered vadose zone in a dry region

Cited by 13 publications

References 50 publications

An Integrated Approach Toward Sustainability via Groundwater Banking in the Southern Central Valley, California

An Integrated Approach Toward Sustainability via Groundwater Banking in the Southern Central Valley, California

Downscaling Groundwater Storage Data in China to a 1-km Resolution Using Machine Learning Methods

Simplified characteristic time method for accurate estimation of the soil hydraulic parameters from one‐dimensional infiltration experiments

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