Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach

Abstract

Abstract. The agricultural sector in Saudi Arabia has witnessed rapid growth in both production and area under cultivation over the last few decades. This has prompted some concern over the state and future availability of fossil groundwater resources, which have been used to drive this expansion. Large-scale studies using satellite gravimetric data show a declining trend over this region. However, water management agencies require much more detailed information on both the spatial distribution of agricultural fields and their varying levels of water exploitation through time than coarse gravimetric data can provide. Relying on self-reporting from farm operators or sporadic data collection campaigns to obtain needed information are not feasible options, nor do they allow for retrospective assessments. In this work, a water accounting framework that combines satellite data, meteorological output from weather prediction models, and a modified land surface hydrology model was developed to provide information on both irrigated crop water use and groundwater abstraction rates. Results from the local scale, comprising several thousand individual center-pivot fields, were then used to quantify the regional-scale response. To do this, a semi-automated approach for the delineation of center-pivot fields using a multi-temporal statistical analysis of Landsat 8 data was developed. Next, actual crop evaporation rates were estimated using a two-source energy balance (TSEB) model driven by leaf area index, land surface temperature, and albedo, all of which were derived from Landsat 8. The Community Atmosphere Biosphere Land Exchange (CABLE) model was then adapted to use satellite-based vegetation and related surface variables and forced with a 3 km reanalysis dataset from the Weather Research and Forecasting (WRF) model. Groundwater abstraction rates were then inferred by estimating the irrigation supplied to each individual center pivot, which was determined via an optimization approach that considered CABLE-based estimates of evaporation and TSEB-based satellite estimates. The framework was applied over two study regions in Saudi Arabia: a small-scale experimental facility of around 40 center pivots in Al Kharj that was used for an initial evaluation and a much larger agricultural region in Al Jawf province comprising more than 5000 individual fields across an area exceeding 2500 km2. Total groundwater abstraction for the year 2015 in Al Jawf was estimated at approximately 5.5 billion cubic meters, far exceeding any recharge to the groundwater system and further highlighting the need for a comprehensive water management strategy. Overall, this novel data–model fusion approach facilitates the compilation of national-scale groundwater abstractions while also detailing field-scale information that allows both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.

Present‐Day Motion of the Arabian Plate

“…The horizontal strain‐rate results suggest that the internal strains building up within the Arabian plate at present have mostly anthropogenic origins. Eight of about nine areas showing measurable strain rates are located either near areas known for groundwater over‐exploitation or rapid urbanization, characterized by karst geomorphology (Amin & Bankher, 1997; Aljammaz et al., 2021; Müller Schmied et al., 2021; López Valencia et al., 2020, Figures 4–6). Despite the spatial correlation between the deforming areas (1) and (6) with suggested structures belonging to the Azraq graben and the Central Arabian graben system we find the re‐activation of these internal structures to be an unlikely driver of the observed strains.…”

Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains

“…Studies have also estimated the irrigation amount by comparing precipitation to remotely sensed ET, such as the MODIS (Moderate Resolution Imaging Spectroradiometer) product (MOD16A). More specifically, MODIS ET, which is treated as the ground truth crop ET rate, surplus over the effective precipitation or Land Surface Model (LSM) simulated ET, is treated as a crop consumptive water use supplied by irrigation [27,[32][33][34][35][36].…”

Land Use/Cover Changes in Al-Jouf, KSA in Response to Water Management Strategies Using Multi-Sensor/-Temporal Data in Google Earth Engine

“…It lies between latitudes 29° 37ʹ 40ʺ and 30° 19ʹ 13ʺ N and between longitudes 37° 58ʹ 30ʺ and 38° 44ʹ 2ʺ E. From the agricultural area and water use point of view, Al-Jouf is considered one of the top five agricultural regions, with the majority area of central pivots and most of the agriculture is managed by large commercial farms. Over the last three decades, the irrigated area in Al-Jouf has increased from being practically non-existent in the 1980s to an area of about 1500 km 2 by 2005 (Valencia et al 2020) and, recently, recognized by the largest modern olive farm in the world. The area has hot desert climatic conditions with an annual average temperature of 22.2 °C and a rainfall average of 59 mm (Youssef et al 2019).…”