An application of the water footprint assessment to optimize production of crops irrigated with saline water: A scenario assessment with HYDRUS

Abstract

Agriculture, due to a growing scarcity of fresh water resources, often uses low-quality waters for irrigation, such as saline waters. However, unmanaged applications of such waters may have negative environmental and economic consequences. Based on the concept of the water footprint (WF), a measure of the consumptive and degradative water use, the field-calibrated and validated HYDRUS (2D/3D) model was applied to find optimal management scenarios (from 1980 different evaluated scenarios). These scenarios were defined as a combination of different salinity rates (SR), irrigation levels (IL, the ratio of an actual irrigation water deth and a full irrigation water depth), nitrogen fertilization rates (NR), and two water-saving irrigation strategies, deficit irrigation (DI) and partial root-zone drying (PRD). The consumptive WF was defined as the crop water consumption divided by the crop yield. The grey WF was calculated for the N fertilizer and defined as the volume of freshwater required to dilute nitrogen (N) in recharge so as to meet ambient water quality standards. Simulated components of water and solute dynamics were used to calculate criteria indices, which were divided into two groups: (a) environmental indices, including the degradative grey water footprint (GWF) and the apparent N recovery rate efficiency (ARE), and (b) economic indices, including economic water (EWP) and land (ELP) productivities. While significant improvements of 3.9-59.2%, 0.1-165.8%, and 0.01-166.5% in ARE, EWP, and ELP, respectively, were obtained when NR varied within the range of 0-200 kg ha −1 , changes in these indices were relatively minor when NR was higher than 200 kg ha −1. At a given NR, GWF tends to increase considerably by up to 180% when DI-crops are subject to low-intermediate salt (SR < 7 dS m −1) and water (IL > 70%) stresses. This is at the expense of up to a 55% reduction in ELP and up to a 120% increase in EWP. With N uptake 0.2-17.3% higher, PRD seems to be a more viable agro-hydrological option than DI in reducing a pollutant load into regional aquifers as well as in sustaining farm economics. The entire analysis reveals that the PRD strategy with N-fertilization rates of 100-200 kg ha ), and irrigation levels of 60-90% represents the best management scenario. It can be concluded that, while there is a substantial need for rescheduling irrigation and fertilization managements when crops are irrigated with saline waters, HYDRUS modeling may be a reliable alternative to extensive field investigations when determining the optimal agricultural management practices.

A comparison of the HYDRUS (2D/3D) and SALTMED models to investigate the influence of various water-saving irrigation strategies on the maize water footprint

“…All considered soil and crop properties, as well as maize grain yield, were also determined at harvest (107 DAS in 2010 and 110 DAS in 2011). A detailed description of various measurements is provided in Karandish and Šimůnek (2018).…”

“…The HYDRUS (2D/3D) model (Šimůnek et al, 2008, 2016) is a powerful numerical model that can simulate soil water and solute dynamics under various irrigation treatments and for different initial and boundary conditions. Karandish and Šimůnek (2016aKarandish and Šimůnek ( , b, 2017Karandish and Šimůnek ( , 2018 employed this model to simulate soil water and solute dynamics under different irrigation treatments during the 2010 and 2011 growing seasons. They provided detailed information on the modeling approach including the model description and governing equations, data requirements by the model, and how these data were collected during the current field investigation.…”

“…Additionally, they provided details about model calibration and validation. Hence, detailed information about the HYDRUS modeling can be found in Karandish and Šimůnek (2016aKarandish and Šimůnek ( , b, 2017Karandish and Šimůnek ( , 2018).…”

“…For each day, the relative contributions of P and I to P+I were used to calculate the green and blue fractions of RO. The fractions of green and blue water in the soil water storage over time were calculated following Chukalla et al 2015; Zhuo et al (2016a), Karandish and Hoekstra (2017); Karandish et al (2018). This method is based on the assumption that the storage of green water in the soil increases when rainfall infiltrates into the soil and that the storage of blue water increases when precipitation infiltrates.…”

Groundwater saving and quality improvement by reducing water footprints of crops to benchmarks levels

“…Water parametrizations to the local context, based on local or field data, would improve trust in the outcomes ( Karandish and Š im ů nek, 2018 ). The use of data sources of differing spatial scales can cause inconsistencies in the results.…”