Groundwater monitoring is fundamental to understanding system dynamics, trends in storage, and the long‐term sustainability of an aquifer. Water‐level data are the key source of information used to understand the response. However, groundwater‐level data are often irregularly sampled, leading to temporal gaps in the record, and are not adequately distributed spatially across an aquifer. This presents challenges when spatially interpolating potentiometric surfaces and creating groundwater maps due to data availability. We present a spatiotemporal kriging methodology to improve spatial and temporal confidence in groundwater‐level predictions at unsampled locations. The space–time data set consists of a trend and residual component modeled with a linear regression and utilize a sum‐metric model to represent spatiotemporal covariances. The Arapahoe aquifer is used as a case study to demonstrate the benefits of spatiotemporal kriging over spatial kriging across a sparsely gauged and irregularly sampled aquifer. The Arapahoe aquifer is a major source of water for many residents along the Rocky Mountain Front Range in Colorado. The results show superior performance of spatiotemporal kriging to predict groundwater levels over the traditional spatial kriging. Spatiotemporal kriging represents realistic temporal and spatial changes in water levels and avoids some of the problems inherent to spatial kriging. This study demonstrates the power of spatiotemporal kriging to help inform system dynamics in irregularly sampled aquifers.

As wildfires in much of the western United States increase in size, frequency, and severity, understanding the impact of these fires on water yield from forested headwater basins is essential to successful management of water resources. The current study examines the changes in partitioning of the hydrologic cycle in the Mill Creek Basin that follow the Chippy Creek Fire in Montana, USA, due to alterations to the vegetative regime. The analysis utilizes remote sensing‐based vegetation indices and evapotranspiration, a model‐interpolated precipitation product, and discharge data to assess annual water budgets and vegetative regimes in the Mill Creek Basin. After being almost 90% burned in the Chippy Creek Fire, vegetation in the catchment has shifted from almost exclusively mixed conifer forest to sagebrush scrubs and grasses. This shift in vegetation is accompanied by abrupt shifts in partitioning of the water budget, resulting in an altered ecohydrologic regime. Post‐fire, evapotranspiration decreases annually by 250 mm (46%), and evaporative fraction decreases by 0.53. However, evapotranspiration product biases may overestimate this decrease from pre‐ to post‐fire. This decrease in evapotranspiration results in an annual increase in streamflow of 136 mm, a 21% increase in the runoff ratio, and a 140% increase in water yield. These changes to the water budget are consistent for 10 years post‐fire and show no trend towards pre‐fire values during the study period. Results will help inform planning and management of water resources downstream of forested catchments that have been impacted by wildfire.

Groundwater (GW) is the primary source of unfrozen freshwater on the planet and in many semi-arid areas, it is the only source of water available during low-water periods. In north-central Chile, there has been GW depletion as a result of semi-arid conditions and high water demand, which has unleashed major social conflicts, some due to drought and others due to agribusiness practices against the backdrop of a private water management model. The Ligua and Petorca watersheds in the Valparaíso Region were studied in order to analyze the influence of climatic and anthropogenic factors on aquifer depletion using an interdisciplinary approach that integrates hydroclimatic variables, remote sensing data techniques, and GW rights data to promote sustainable GW management. The Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) were calculated and the 2002–2017 land-use change was analyzed. It was shown that GW decreased significantly (in 75% of the wells) and that the hydrological drought was moderate and prolonged (longest drought in the last 36 years). The avocado-growing area in Ligua increased significantly—by 2623 ha—with respect to other agricultural areas (higher GW decrease), while in Petorca, it decreased by 128 ha. In addition, GW-rainfall correlations were low and GW rights were granted continuously despite the drought. The results confirmed that aquifer depletion was mostly influenced by human factors due to overexploitation by agriculture and a lack of water management.

The Denver Basin Aquifer System (DBAS) is a critical groundwater resource along the Colorado Front Range. Groundwater depletion has been documented over the past few decades due to the increased water use among users, presenting long‐term sustainability challenges. A spatiotemporal geostatistical analysis is used to estimate potentiometric surfaces and evaluate groundwater storage changes between 1990 and 2016 in each of the four DBAS aquifers. Several key depletion patterns and spatial water‐level changes emerge in this work. Hydraulic head changes are the largest in the west‐central side of the DBAS and have decreased in some areas by up to 180 m since 1990, while areas to the northwest show increases in hydraulic head by over 30.5 m. The Denver and Arapahoe aquifers show the largest groundwater storage losses, with the highest rates occurring in the 2000s. The results highlight uncertainty in the volumetric predictions under various storage coefficient calculations and emphasize the importance of representative aquifer characterization. The observed groundwater storage depletions are due to a combination of factors, which include population growth increasing the demand for water, variable precipitation, and drought influencing recharge, and increased groundwater pumping. The methods applied in this study are transferable to other groundwater systems and provide a framework that can help assess groundwater depletion and inform management decisions at other locations.

A multi-layer surface energy balance model was previously developed to estimate crop transpiration (T) and soil evaporation (E) in orchards partially wet by micro-irrigation systems. The model, referred to as SEB-PW, estimates latent (λE), sensible (H), and soil heat fluxes (G) and separates actual evapotranspiration (ETa) into dry and wet soil E and crop T. The main goal of this work was to evaluate the ability of the SEB-PW model to estimate ETa and analyze the diurnal and seasonal dynamics of E and T in two hazelnut (Corylus avellana L.) orchards irrigated by drip or micro-sprinkler systems. The assessment showed that simulated hourly ET was highly correlated with estimates from nearby weather stations and with measurements from micro-lysimeters (MLs). Hourly ET estimates were evaluated by root-mean-square error (RMSE), mean absolute error (MAE), the Nash–Sutcliffe coefficient (NSE), and the index of agreement (da), which equaled 58.6 W m−2, 35.6 W m−2, 0.85, and 0.94, respectively. Daily E estimates were also evaluated and equaled 0.27 mm day−1, 0.21 mm day−1, 0.87, and 0.94, respectively, and obtained a coefficient of determination (r2) of 0.85 when compared to the measurements from the MLs. Within a day of irrigation, E accounted for 28 and 46% of ET. In accordance with the obtained results, the proposed SEB-PW model improves estimates of soil E by allowing the wetted and non-wetted areas to be estimated separately, which could be useful for optimizing irrigation methods and practices in hazelnut orchards.