DRAINMOD simulation of paddy field drainage strategies and adaptation to future climate change in lower reaches of the Yangtze river basin^*

Abstract

The DRAINMOD model was used to simulate the current and future water balance in the Yanyun Irrigation District, China. Projections of future climate in the district (2021:2050) show that annual maximum and minimum temperatures will increase by [1.09 and 1.15 °C] under the representative concentration pathway RCP4.5 and [1.34 and 1.39 °C] under RCP8.5, besides more frequency of one‐day peak precipitation events. DRAINMOD simulations revealed that future annual runoff will increase by 33.3% (RCP4.5) and 36.9% (RCP8.5), while groundwater tables will drop by 6% (RCP4.5) and 14.5% (RCP8.5). Future hydrology has been resimulated, but with increasing the capacity of surface depressions in an attempt to minimize adverse impacts of climate change, and results have been checked twice: under proper and improper subsurface drainage practices. Under proper subsurface drainage practices, it was revealed that future runoff will decrease by 25.3% (RCP4.5) and 23.6% (RCP8.5), which will cause a rise in groundwater tables to desired levels, while in contrast, improper subsurface drainage practices will increase future runoff by 13.7% (RCP4.5) and 2.8% (RCP8.5), all compared to future values before adaptation. Therefore, proper drainage strategies are a vital tool that helps to cope with climate change in agricultural lands and mitigate future runoff rates.

Assessment of Subsurface Drainage Strategies Using DRAINMOD Model for Sustainable Agriculture: A Review

“…This could cause the model to produce improper predictions of the farmland water balance during the periods of mid-summer drainage practices (when the surface depression capacity varies due to agricultural practices). To assess such a problem, we review the results of the study conducted by Awad et al [15], who applied the DRAINMOD model to predict the water fate in a paddy area that has mid-summer drainage practices. We aim to focus on the period during which the surface depression capacity changes.…”

“…So, there is no option in the model to consider any changes in the capacity of surface depression (such as under mid-summer drainage practices). Since the surface depression capacity is a major determinant of the water fate in farmlands [15,16], the DRAINMOD model's shortage in considering changes in the surface depression capacity may cause the model to produce improper water distribution patterns in agricultural lands. Therefore, this paper reviews the DRAINMOD model's performance in the study conducted by Awad et al [15], who applied the model to predict Among all known methodologies and approaches for assessing the performance of subsurface drainage systems, mathematical models are superior since they save costs and time.…”

“…Since the surface depression capacity is a major determinant of the water fate in farmlands [15,16], the DRAINMOD model's shortage in considering changes in the surface depression capacity may cause the model to produce improper water distribution patterns in agricultural lands. Therefore, this paper reviews the DRAINMOD model's performance in the study conducted by Awad et al [15], who applied the model to predict Among all known methodologies and approaches for assessing the performance of subsurface drainage systems, mathematical models are superior since they save costs and time. DRAINMOD is one of the models that allow the quantification, on a continuous basis, of the performance of drainage and other related water management systems, as well as the assessment of various impacts of several field conditions and management practices on the performance of subsurface drainage systems [7,12].…”

“…Since the surface depression capacity is a major determinant of the water fate in farmlands [15,16], the DRAINMOD model's shortage in considering changes in the surface depression capacity may cause the model to produce improper water distribution patterns in agricultural lands. Therefore, this paper reviews the DRAINMOD model's performance in the study conducted by Awad et al [15], who applied the model to predict the water fate in a paddy area where the surface depression capacity varies during the growing season due to mid-summer drainage practices. The aim is to investigate whether or not it is necessary to modify the input module of the DRAINMOD model and include the surface depression capacity as a time-variable value.…”

Reversing the Negative Effects of Poor Agricultural Drainage Using Risks Management

“…If fertilizers are applied incorrectly, there is a signi cant risk that they will contaminate groundwater in waterlogged areas where groundwater tables are high enough to reach the topsoil layers, drastically reducing water quality (Ashraf et al, 2019; Srivastav, 2020 and Abd-Elaty et al, 2020). Numerous studies have suggested that farmlands with shallow water tables are more vulnerable to groundwater contamination (Awad et al, 2021).…”