Crop growth depends on the root-zone soil
moisture (RZSM) (~top 1m). Accurate estimation of RZSM is
vital to optimize irrigation management for saving water and
energy while sustaining crop yield. The High-Resolution Land
Assimilation System (HRLDAS) from NCAR can generate
RZSM at field scales for irrigation management. The soil
moisture data from various agriculture sites in the AmeriFlux
network, U.S. Climate Reference Network (USCRN), and Soil
Climate Analysis Network (SCAN) are used to verify the soil
moisture products generated by HRLDAS. Although the
HRLDAS products is not location specific and could be
applied nationwide, this study will focus on Nebraska for
evaluation, validation, and further calibration. We also
compared NASA’s SMAP surface soil moisture products to
HRLDAS surface layer soil moisture. Since the accuracy of
the SMAP product is known, this comparison directly
validates the HRLDAS surface soil moisture product and
indirectly validate its RZSM products. Results from these two
validation methods show a good accuracy of HRLDAS soil
moisture products. The conspicuous differences between
HRLDAS and SMAP products indicate that HRLDAS omits
the irrigation activities as its simulation is based on weather
variables and energy balance. It’s hard for HRLDAS to
consider and include the irrigation actions in its results, while
as SMAP products remotely sense the soil moisture as it is, the
changes caused by irrigation are clearly reflected. Therefore,
a simple calibration is applied to the HRLDAS products by
including irrigation amount as its variables.
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An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration
Given the increasing prevalence of droughts, unpredictable rainfall patterns, and limited access to dependable water sources in the United States and worldwide, it has become crucial to implement effective irrigation scheduling strategies. Irrigation is triggered when some variables, such as soil moisture or accumulated water deficit, exceed a given threshold in the most common approaches applied in irrigation scheduling. A High-Resolution Land Data Assimilation System (HRLDAS) was used in this study to generate timely and accurate soil moisture and evapotranspiration (ET) data for irrigation management. By integrating HRLDAS products and the crop growth model (AquaCrop), an automated data-driven irrigation scheduling approach was developed and evaluated. For HRLDAS ET and soil moisture, the ET-water balance (ET-WB)-based method and soil-moisture-based method were applied accordingly. The ET-WB-based method showed a 10.6~33.5% water-saving result in dry and set seasons, whereas the soil moisture-based method saved 7.2~37.4% of irrigation water in different weather conditions. Both of these methods demonstrated good results in saving water (with a varying range of 10~40%) without harming crop yield. The optimized thresholds in the two approaches were partially consistent with the default values from the Food and Agriculture Organization and showed a similar trend in the growing season. Furthermore, the forecasted rainfall was integrated into this model to see its water-saving effect. The results showed that an additional 10% of irrigation water, which is 20~50%, can be saved without harming the crop yield. This study automated the data-driven approach for irrigation scheduling by taking advantage of HRLDAS products, which can be generated in a near-real-time manner. The results indicated the great potential of this automated approach for saving water and irrigation decision making.
more » « less- Award ID(s):
- 1739705
- PAR ID:
- 10483299
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Sustainability
- Volume:
- 15
- Issue:
- 17
- ISSN:
- 2071-1050
- Page Range / eLocation ID:
- 12908
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Soil salinization is a global phenomenon that affects large tracts of arid farmland worldwide. It contributes to the loss of soil fertility, declining yields, and – in the most severe cases – land unsuitability for cultivation. Irrigation water applications are both the main cause of and the solution to, anthropogenic (or ‘secondary’) salinization because salt typically enters the soil column as dissolved in irrigation water and leaves it through excess water applications (e.g., leaching). Excess leaching, which places additional water costs in areas affected by water scarcity, can be achieved with different irrigation techniques and practices. Here, by complementing a process-based crop water model with a salt balance of the shallow soil, we investigate the tradeoff between root zone salinization and water conservation to limit withdrawals from the water source. We evaluate how such a tradeoff is achieved under different irrigation technology and excess leaching practices. Considering as a case study the cultivation of tomatoes in Egypt, we find that drip and furrow irrigation allows for better control of salt accumulation, thus preventing crop exposure to salt stress. Drip irrigation achieves this goal with minimal water applications because it maintains the soil wetter. Thus, the (rare) rainfall events find more suitable conditions to drain the excess moisture. Conversely, by using more irrigation water (and ‘less efficiently’), furrow irrigation allows for higher rates of soil drainage and salt leaching. The irrigation schedule typically adopted with sprinkler irrigation allows for soil drying, thus limiting the ability of rainfall events to drain the soil and leach its salts. Collectively, these results highlight the key role of irrigation technology and practices in the management of secondary salinity in dryland agriculture. Specifically, there is a tradeoff between minimizing water use and preventing salt accumulation in the root zone. Drip irrigation exhibits the co-benefit of achieving both goals, while furrow irrigation limits soil salinity at the cost of requiring greater volumes of applied irrigation water.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/su151712908
