Cascading Dynamics of the Hydrologic Cycle in California Explored through Observations and Model Simulations

Abstract

As drought occurs in a region it can have cascading effects through the water cycle. In this study, we explore the temporal co-evolution of various components of the hydrologic cycle in California from 2002 to 2018. We combine information from the Gravity Recovery and Climate Experiment (GRACE) satellites, the North American Land Data Assimilation System (NLDAS) suite of models, and the California Department of Water Resources (DWR) reservoir levels to analyze dynamics of Total Water Storage (TWS), soil moisture, snow pack, large reservoir storage, and ultimately, groundwater. For TWS, a trend of −2 cm/yr is observed during the entire time period of our analysis; however, this rate increases to about −5 cm/yr during drought periods (2006−2010 and 2012−2016). Results indicate that the majority of the loss in TWS is caused by groundwater depletion. Using proper error accounting, we are able to identify the start, the peak, and the ending of the drought periods for each individual water state variable in the study domain. We show that snow and soil moisture are impacted earlier and recover faster than surface water and groundwater. The annual and year-to-year dynamics shown in our results portray a clear cascading effect of the hydrologic cycle on the scale of 8−16 months.

Response of Vegetation to Changes in Temperature and Precipitation at a Semi-Arid Area of Northern China Based on Multi-Statistical Methods

“…Additionally, similar to NDVI-T, the harvest work could be the key reason for reducing the leaf cover and a lower tail relationship (Clayton Copula) between the NDVI and precipitation in the upstream, during the early autumn. Furthermore, the utilization of ground water resource in the upstream could accelerate the depletion of the available water for vegetation growth, especially in the autumn with less rainfall to replenish the ground water in semi-arid area [36]. The lack of a causal relation for the midstream sub-watershed, may due to the great amount of ground water conservation ability, which could help the vegetation to prevent drought or flood for a stable growth rate [30].…”

“…It is acknowledged that over-grazing and over-cultivation were two major causes of reduced vegetative growth, especially in semi-arid areas, where the ecosystem is fragile [43]. Over-grazing would threaten vegetation species composition, variety and richness [44], while the over-cultivation may significantly deplete ground water for both human and crops [36]. In our study catchment, owing to the Grain for Green Program and environmental protection regulation since 1962, grazing and cultivation activities have been limited.…”

Groundwater Depletion Signals in the Beqaa Plain, Lebanon: Evidence from GRACE and Sentinel-1 Data

“…Additionally, other variables in the hydrologic cycle are also impacted by a changing climate, such as soil moisture or snow packs, which are affected by increasing temperatures and precipitation variability [7][8][9]. The effects of unsustainable use of groundwater resources and resultant groundwater depletion have been observed through satellite measurements and/or model simulations in many systems of the world [6,[10][11][12], but consistent monitoring of groundwater is still lacking.…”

“…In recent years, satellite data has emerged as a great tool to observe the Earth, including certain variables in the hydrologic cycle [5,[10][11][12]23,24]. For example, NASA's Gravity Recovery and Climate Experiment (GRACE) satellites [25] have been established as extremely valuable instruments for regional to global scale water cycle studies [6,26].…”

“…To obtain information on groundwater dynamics, gravimetric observations from GRACE are obtained and the signal is translated into a mass change signal, which can then be directly related to changes in freshwater sources. To estimate groundwater storage changes, information on other hydrological variables, obtained from in-situ data or model simulations, can be combined with information from the GRACE signal (e.g., [6,[10][11][12][13]). Typically, the hydrologic variables that are needed for this problem include snow water equivalent and freshwater stored in soil moisture, and this information can be acquired from model simu-lations.…”