Simulated Irrigation Water Research Articles

Climate Impact on Irrigation Water Use in Jiangsu Province, China: An Analysis Using Empirical Mode Decomposition (EMD)

In this paper, the quantitative effects of climatic factor changes on irrigation water use were analyzed in Jiangsu Province from 2004 to 2020 using the Empirical Mode Decomposition (EMD) time-series analysis method. In general, the irrigation water use, precipitation (P), air temperature (T), wind speed (Ws), relative humidity (Rh) and water vapor pressure (Vp) annual means ± standard deviation were 25.44 ± 1.28 billion m3, 1034.4 ± 156.6 mm, 16.1 ± 0.4 °C, 2.7 ± 0.2 m·s−1, 74 ± 2%, and 15.5 ± 0.6 hPa, respectively. The analysis results of the irrigation water use sequence using EMD indicate three main change frequencies for irrigation water use. The first major change frequency (MCF1) was a 2-to-3-year period varied over a ±1.00 billion m3 range and showed a strong correlation with precipitation (the Pearson correlation was 0.68, p < 0.05). The second major change frequency (MCF2) was varied over a ±2.00 billion m3 range throughout 10 years. The third major change frequency (MCF3) was a strong correlation with air temperature, wind speed, relative humidity, and water vapor pressure (the Pearson correlations were 0.56, 0.75, 0.71, and 0.69, respectively, p < 0.05). In other words, MCF1 and MCF3 represent the irrigation water use changes influenced by climate factors. Furthermore, we developed the Climate–Irrigation–Water Model based on farmland irrigation theory to accurately assess the direct effects of climate factor changes on irrigation water use. The model effectively simulated irrigation water use changes with a root mean square error (RMSE) of 0.06 billion m3, representing 2.24% of the total. The findings from the model indicate that climate factors have an average impact of 6.40 billion m3 on irrigation water use, accounting for 25.14% of the total. Specifically, precipitation accounted for 3.04 billion m3 of the impact, while the combined impact of other climatic factors was 3.36 billion m3.

Implementation and Evaluation of Irrigation Techniques in the Community Land Model

AbstractSeveral previous studies have highlighted the irrigation‐induced impacts on the global and regional water cycle, energy budget, and near‐surface climate. While land models are widely used to address this question, the implementations of irrigation in these models vary in complexity. Here, we expand the representation of irrigation in Community Land Model to enable six different irrigation methods. We find that using a combination of irrigation methods, including default, sprinkler, flood and paddy techniques performs best as determined by evaluating the simulated irrigation water withdrawals against observations, and therefore select this combination as the new irrigation scheme. Then, the impact of the new irrigation scheme on surface fluxes is evaluated and detected using single‐point simulations. Finally, the global and regional irrigation‐induced impacts on surface energy and water fluxes are compared using both the original and the new irrigation scheme. The new irrigation scheme substantially reduces the bias and root‐mean‐square error of simulated irrigation water withdrawal in the USA and other countries, but considerably overestimates withdrawals in Central China. Results of single‐point experiments show that different irrigation methods have different effects on surface fluxes, while the magnitudes are small. At the global scale, the new scheme enlarges the irrigation‐induced impacts on water and energy variables relative to the original scheme, with varying magnitudes across regions. Overall, our results suggest that this newly developed scheme is a better tool for simulating irrigation‐induced impacts on climate, and highlight the added value of incorporating human water management in Earth system models.

Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality

Abstract. This paper describes the University of New Hampshire Water Balance Model, WBM, a process-based gridded global hydrologic model that simulates the land surface components of the global water cycle and includes water extraction for use in agriculture and domestic sectors. The WBM was first published in 1989; here, we describe the first fully open-source WBM version (v.1.0.0). Earlier descriptions of WBM methods provide the foundation for the most recent model version that is detailed here. We present an overview of the model functionality, utility, and evaluation of simulated global river discharge and irrigation water use. This new version adds a novel suite of water source tracking modules that enable the analysis of flow-path histories on water supply. A key feature of WBM v.1.0.0 is the ability to identify the partitioning of sources for each stock or flux within the model. Three different categories of tracking are available: (1) primary inputs of water to the surface of the terrestrial hydrologic cycle (liquid precipitation, snowmelt, glacier melt, and unsustainable groundwater); (2) water that has been extracted for human use and returned to the terrestrial hydrologic system; and (3) runoff originating from user-defined spatial land units. Such component tracking provides a more fully transparent model in that users can identify the underlying mechanisms generating the simulated behavior. We find that WBM v.1.0.0 simulates global river discharge and irrigation water withdrawals well, even with default parameter settings, and for the first time, we are able to show how the simulation arrives at these fluxes by using the novel tracking functions.

Simulated irrigation water productivity and related profit effects in U.S. Southern High Plains cotton production

To explore management practices that increase irrigation water productivity (IWP) in U.S. Southern High Plains (SHP) cotton production, the CROPGRO-Cotton crop simulation model was used to evaluate the yield, IWP, and profit effects of irrigation amount and timing. Using 2005–2019 weather input data from 21 SHP weather stations, lint yields were simulated for each of the 315 station-years under unirrigated ‘dryland’ conditions and 18 increasing total irrigation (TIRR) levels. As TIRR was increased to 55.9 cm median lint yields asymptotically approached a maximum. However, irrigation above 35.6 cm increased the incidence of total irrigation plus growing season rainfall exceeding 100% of potential crop ET, leading to decreasing marginal yield effects and decreasing IWP. The highest median IWP (0.321 kg m−3) was found with both 33.0 and 35.6 cm of total irrigation, with 30.5 cm providing slightly lower IWP (0.320 kg m−3). In analyses of irrigated profitability under varying lint price and pumping cost conditions, 30.5 cm (12.0 in) of irrigation increases profits relative to dryland conditions under all but low lint price and high pumping cost conditions. But as TIRR is reduced the probability of these positive profit effects become similar to an evenly weighted coin flip at about 17.8 cm (7.0 in). Simulations that varied the timing of 30.5 cm of irrigation increased median IWP up to 0.434 kg m−3 by limiting irrigation to cotton’s reproductive and maturation periods, with no irrigation during the initial vegetative period. As a result, these simulations show that applying 30.5–35.6 cm (12.0–14.0 in) of irrigation during cotton’s reproductive and maturation phases, with little or no vegetative irrigation, maximizes IWP in SHP cotton production under current climate conditions.

Unreconciled effects of salinity on draining and wetting functions in unsaturated soils

AbstractIn a sequence of one‐step outflow–inflow experiments, this study examines the effects of salinity on soil hydraulic properties with the goal of developing a better understanding of how to predict salinity's impacts on soils. The results of this study are compared with estimates obtained using the Hydrus‐1D model for soil water and solute transport. The model assumes a decline in hydraulic conductivity (K), caused by solution chemistry, is constant over the entire hydraulic conductivity function [K(θ)] and equal to a constant reduction factor established at saturation. In contrast with the model assumptions, the results of this study show an increase in the solution chemistry's effect on K with decreasing soil moisture (θ). These findings demonstrate that current models that exclude solution chemistry, or models that assume a constant K reduction for the entire K(θ) function, may be overestimating drainage, recharge, or bare soil evaporation. This research used undisturbed soil cores and simulated irrigation water with decreasing electrical conductivity (EC) from 20 to 0.25 dS m–1 and sodium adsorption ratio (SAR) held constant. Changes in K(θ) were observed only after dropping below an EC of 1.5 dS m–1, which is consistent with past studies. At reduced soil water contents, however, K(θ) decreased by up to five orders of magnitude relative to native soils. A second experiment was conducted that increased the SAR from 4 to ≥20, held EC constant at 0.65 dS m–1, and displayed only moderate reductions in K(θ), although K was reduced proportionally more at reduced soil water contents. Therefore, based on the observed results, an integrated K(EC,θ) and K(SAR,θ) model is needed to better predict salinity effects on soil hydraulic properties and is increasingly important as freshwater resources decline.

Optimization of irrigation scheduling for barley crop, combining AquaCrop and MOPECO models to simulate various water-deficit regimes

To optimize the irrigation scheduling of field crops to maximize irrigation water productivity requires expert knowledge of the crop development and its productive response to water deficit. Implementing this idea with commodities such as barley, whose current global profitability is low, and, more specifically, in areas where the availability of water resources for irrigation is limited, requires a proper decision support system. In this research, AquaCrop and MOPECO models were used to compute and compare both the crop-water production and irrigation water productivity functions generated by several irrigation strategies provided by each model for the typical irrigated crop barley grown in the area. Furthermore, we evaluated both models’ performance with a 3-year field experiment applying the methodology of optimized regulated deficit irrigation for limited volumes of irrigation water (ORDIL) in barley crop. The results obtained from the production functions show that gross irrigation water depths (GIWD) of more than 310 mm can be useful to attain the potential crop yield, depending on the criteria considered to generate the irrigation scheduling. However, with less GIWD available, the simulated barley development was subjected to water deficit, leading to a reduction in both crop yield and irrigation water productivity. Thus MOPECO simulated higher crop yields and irrigation water productivity values than those obtained by AquaCrop, being between 16% and 27% for crop yields and between 8.0% and 27.5% for irrigation water productivity, under similar GIWD levels. These differences are mainly due to how the irrigation strategies are outlined in the two models and the different evapotranspiration methodologies they deploy. Finally, both models provided performed appropriately in simulating final crop yield (errors lower than 0.50 × 103 kg ha−1), as well as canopy cover and aboveground biomass evolution, in the case of AquaCrop, whose goodness of fit indicators were close to 0.90 or higher. In terms of crop evapotranspiration, AquaCrop simulated a 12% higher average value than MOPECO. It can be concluded that both models are complementary, and their use will depend on the necessities of the final user. Thus, MOPECO offers a wider range of irrigation strategies, while AquaCrop offers a more detailed information about the physiological response of the crop during its development, being the results of the simulations accurate enough in both models.

Relating agriculture, energy, and water decisions to farm incomes and climate projections using two freeware programs, FEWCalc and DSSAT

CONTEXTThe larger scale perspective of Integrated Assessment (IA) and smaller scale perspective of Impacts, Adaptation, and Vulnerability (IAV) need to be bridged to design long-term solutions to agricultural problems that threaten agricultural production, rural economic viability, and global food supplies. FEWCalc (Food-Energy-Water Calculator) is a new freeware, agent-based model with the novel ability to project farm incomes based on crop selection, irrigation practices, groundwater availability, renewable energy investment, and historical and projected environmental conditions. FEWCalc is used to analyze the interrelated food, energy, water, and climate systems of Finney County, Kansas to evaluate consequences of choices currently available to farmers and resource managers. OBJECTIVEThis article aims to evaluate local farmer choices of crops and renewable energy investment in the face of water resource limitations and global climate change. Metrics of the analysis include agricultural and renewable-energy production, farm income, and water availability and quality. The intended audience includes farmers, resource managers, and scientists focusing on food, energy, and water systems. METHODSData derived from publicly available sources are used to support user-specified FEWCalc input values. DSSAT (Decision Support System for Agrotechnology Transfer) with added arid-region dynamics is used to obtain simulated crop production and irrigation water demand for FEWCalc. Here, FEWCalc is used to simulate agricultural and energy production and farm income based on continuation of recent ranges of crop prices, farm expenses, and crop insurance; continuation of recent renewable-energy economics and government incentives; one of four climate scenarios, including General Circulation Model projections for Representative Concentration Pathway 8.5; and groundwater-supported irrigation and its limitations. RESULTS AND CONCLUSIONSA 50-year (2018-2067) climate and groundwater availability projection process indicates possible trends of future crop yield, water utility, and farm income. The simulation during more wet years produces high crop production and slower depletion of groundwater, as expected. However, surprisingly, the simulations suggest that only the Drier Future scenario is commercially profitable, and this is because of reduced expenses for dryland farming. Although simulated income losses due to low crop production are ameliorated by the energy sector income and crop insurance, the simulation under climate change still produces the worst annual total income. SIGNIFICANCEFEWCalc addresses scientific, communication, and educational gaps between global- and local-scale FEW research communities and local stakeholders, affected by food, energy, water systems and their interactions by relating near-term choices to near- and long-term consequences. This analysis is needed to craft a more advantageous future.

Biochars reduce irrigation water sodium adsorption ratio

Irrigation water quality plays a vital role in sustaining crop productivity and feeding a growing world population. In many countries, continued agricultural water reuse can lead to greater water-soluble salt concentrations, and in particular Na; finding means by which irrigation water Na, and thus sodium adsorption ratios (SAR), can be reduced would reduce the rate at which soil sodification occurs. Four biochars, containing a variety of organic functional groups and electrochemistries, were examined for their potential to sorb and remove Na from simulated irrigation water, and subsequently reduce water SAR. Two batch experiments examined the role that wheat straw biochar, lodgepole pine biochar, Kentucky bluegrass biochar, and hemp biochar played in terms of sorbing sodium over time or application rate. Of the four biochars examined, hemp biochar had the lowest oxidation–reduction potential (ORP; ~ 0–100 mV), sorbed the greatest Na amount (up to 923 mg kg−1), and released Ca and Mg (up to 115 and 63 mg kg−1, respectively) into solution, all of which led to a significant reduction in water SAR (from 8.8 to 7.3; 17% decrease). Sodium sorption onto hemp biochar better fit a Langmuir versus a Freundlich isotherm, yet followed a pseudo-second-order model better than a pseudo-first-order kinetic model. The data suggest that Na ions formed a monolayer on the hemp biochar surface, influenced by associations with π electrons, but given time the Na ions may diffuse into biochar pores or more slowly interact with biochar-borne π electrons. Hemp biochar shows promise in reducing the SAR of Na-impacted waters. Future investigations should focus on additional laboratory, greenhouse, and field trials with hemp biochar and other biochars designed to have similar or superior properties for sorbing excess irrigation water Na and improving crop growth.

Comparison of the Relative Efficacies of Granulated Activated Carbon and Biochar to Reduce Chlorpyrifos and Imidacloprid Loading and Toxicity Using Laboratory Bench Scale Experiments.

Pesticide loads and associated toxicity can be significantly reduced using integrated vegetated treatment systems, which remove moderately soluble and hydrophobic pesticides, but need a sorbent material to remove more soluble pesticides. Neonicotinoids such as imidacloprid are widely used insecticides, acutely toxic, and have been linked to a range of ecological effects. Laboratory experiments were conducted to test the sorptive capacity of granulated activated carbon and biochar for removing imidacloprid and the organophosphate insecticide chlorpyrifos in a scaled-down treatment system. Simulated irrigation water spiked with individual pesticides was treated with a bench-top system designed to mimic a 600 L carbon installation receiving 108,000 L of flow per day for sixteen days. Biochar reduced insecticides to less than detectable and non-toxic levels. Granulated activated carbon similarly reduced chlorpyrifos, but allowed increasing concentrations of imidacloprid to break through. Both media treated environmentally relevant concentrations, and would be effective if used under conditions with reduced particle loads.

Assessing the Climate Change Impacts on Grain Sorghum Yield and Irrigation Water Use under Full and Deficit Irrigation Strategies

HighlightsIrrigated grain sorghum yield and irrigation water use decreased under climate change.Increase in growing season temperature beyond 26°C resulted in a sharp decline in grain sorghum yield.Irrigating during early reproductive stages resulted in the most efficient use of limited water.Irrigating to replenish soil water to 80% of field capacity was found suitable for both current and future climates. Groundwater overdraft from the Ogallala Aquifer for irrigation use and anticipated climate change impacts pose major threats to the sustainability of agriculture in the Texas High Plains (THP) region. In this study, the DSSAT-CSM-CERES-Sorghum model was used to simulate climate change impacts on grain sorghum production under full and deficit irrigation strategies and suggest optimal deficit irrigation strategies. Two irrigation strategies were designed based on (1) crop growth stage and (2) soil water deficit. For the first strategy, seven deficit irrigation scenarios and one full irrigation scenario were simulated: three scenarios with a single 100 mm irrigation scheduled between panicle initiation and boot (T1), between boot and early grain filling (T2), and between early and late grain filling (T3) growth stages; three 200 mm irrigation treatments with combinations of T1 and T2 (T4), T1 and T3 (T5), and T2 and T3 (T6); one 300 mm irrigation scenario (T7) that was a combination of T1, T2, and T3; and a full irrigation scenario (T8) in which irrigation was applied throughout the growing season to maintain at least 50% of plant-available water in the top 30 cm soil profile. For the second strategy, the irrigation schedule obtained from auto-irrigation (T8) was mimicked to create a full irrigation scenario (I100) and six deficit irrigation scenarios. In the deficit irrigation scenarios, water was applied on the same dates as scenario I100; however, the irrigation amounts of scenario I100 were reduced by 10%, 20%, 30%, 40%, 50%, and 60% to create deficit irrigation scenarios I90, I80, I70, I60, I50, and I40, respectively. Projected climate forcings were drawn from nine global climate models (GCMs) and two representative concentration pathways (RCP 4.5 and RCP 8.5). Climate change analysis indicated that grain sorghum yield under full irrigation was expected to be reduced by 5% by mid-century (2036 to 2065) and by 15% by late-century (2066 to 2095) under RCP 8.5 compared to the baseline period (1976 to 2005). Simulated future irrigation water demand of grain sorghum was reduced due to the shorter growing season and improved dry matter- and yield-transpiration productivity, likely due to CO2 fertilization. Based on the simulated grain sorghum yield and irrigation water use efficiency, the most efficient use of limited irrigation was achieved by applying irrigation during the early reproductive stages of grain sorghum (panicle initiation through early grain filling). A 20% deficit irrigation scenario was found to be optimal for current and future conditions because it was more water use efficient than full irrigation with a minor yield reduction of <11%. In summary, these results indicated that strategic planning of when and how much to irrigate could help in getting the most out of limited irrigation. Keywords: CERES-Sorghum, Critical growth stages, Crop yield, Global climate model, Irrigation demand, Soil water depletion.

Decontamination of irrigation water using a combined sand filtration and UV‐C light treatment

AbstractSurface irrigation water is a food safety risk due to susceptibility to contamination and varying turbidity that affects chlorination efficacy. Effectiveness of a combined high‐throughput, commercially available sand filter and UV‐C system to inactivate Escherichia coli (K12, and attenuated O157:H7) in simulated irrigation water of varying turbidity and actual irrigation water was investigated. Sand filtration reduced the water turbidity from ~600 nephelometric turbidity units (NTU) to ~200 NTU but did not effectively filter out E. coli (K12) [<1 log colony forming units (CFU)/ml]. UV‐C‐induced inactivation of E. coli (attenuated O157:H7) was modeled for various levels of turbidity (0–500 NTU), and the relationship between the D value for inactivation and turbidity was found to be linear (R2 > .97). Predicted UV treatment time to achieve 5 log reduction in water with turbidities of 100 and 300 NTU was 110 and 370 s, respectively. Validation performed with irrigation water (turbidity of 330 ± 82 NTU) showed that sand filtration reduced turbidity to 180 ± 57 NTU. Based on this, the duration of UV treatment required for 5 log reduction of E. coli O157:H7 was calculated (average of 237 s). Observed levels of inactivation, 4.7 ± 0.31 log CFU/ml, were not significantly different (p > .05) from the predicted level, 5 log CFU/ml, indicating a good model fit.

Effects of soil- and climate data aggregation on simulated potato yield and irrigation water requirement

Input data aggregation affects crop model estimates at the regional level. Previous studies have focused on the impact of aggregating climate data used to compute crop yields. However, little is known about the combined data aggregation effect of climate (DAEc) and soil (DAEs) on irrigation water requirement (IWR) in cool-temperate and spatially heterogeneous environments. The aims of this study were to quantify DAEc and DAEs of model input data and their combined impacts for simulated irrigated and rainfed yield and IWR. The Agricultural Production Systems sIMulator Next Generation model was applied for the period 1998–2017 across areas suitable for potato (Solanum tuberosum L.) in Tasmania, Australia, using data at 5, 15, 25 and 40 km resolution. Spatial variances of inputs and outputs were evaluated by the relative absolute difference (rAD¯) between the aggregated grids and the 5 km grids. Climate data aggregation resulted in a rAD¯ of 0.7–12.1%, with high values especially for areas with pronounced differences in elevation. The rAD¯ of soil data was higher (5.6–26.3%) than rAD¯ of climate data and was mainly affected by aggregation of organic carbon and maximum plant available water capacity (i.e. the difference between field capacity and wilting point in the effective root zone). For yield estimates, the difference among resolutions (5 km vs. 40 km) was more pronounced for rainfed (rAD¯ = 14.5%) than irrigated conditions (rAD¯ = 3.0%). The rAD¯ of IWR was 15.7% when using input data at 40 km resolution. Therefore, reliable simulations of rainfed yield require a higher spatial resolution than simulation of irrigated yields. This needs to be considered when conducting regional modelling studies across Tasmania. This study also highlights the need to separately quantify the impact of input data aggregation on model outputs to inform about data aggregation errors and identify those variables that explain these errors.

Modifying Automatic Irrigation in SWAT for Plant Water Stress scheduling

Automatic irrigation in the Soil and Water Assessment Tool (SWAT) is triggered by using plant water stress and soil water deficit irrigation scheduling. Auto-irrigation is important to simulate the catchment’s behavior in response to climate change and water management scenarios. However, studies have identified deficiencies in the auto-irrigation algorithms in SWAT as the irrigation water amount simulated under plant water stress scheduling shows a large deviation from the simulated irrigation water amount under soil water deficit scheduling. Therefore, the current research deals with validating and modifying the auto-irrigation scheduling under plant water stress condition using SWAT. The modified SWAT model was evaluated against the Soil-Water-Atmosphere-Plant (SWAP) model as well as observed data for irrigation and crop yield at an experimental field (Hamerstorf, Lower Saxony, Germany) during the 2008–2018 cropping seasons. The two SWAT subroutines. swu and. autoirr were modified. The existing root density distribution function was replaced with the one proposed by Li et al. (1998) and also a dynamic estimation of the plant water uptake compensation factor (EPCO) was incorporated into the modified SWAT. The results revealed that SWAP and modified SWAT were able to simulate the irrigation amount and crop yield with an acceptable bias for all the crops at the experimental site. However, the overall spread of crop yield simulated (11 years) by both the models was less compared to the observed spread for most of the crops. Furthermore, the modified SWAT code was used to simulate the irrigation amount for three different agro-climatic catchments in Germany, India and Vietnam. Results showed improved irrigation simulation in terms of long-term annual amounts compared to the default SWAT under plant water stress condition.

Climate change impact on the hydrological budget of a large Mediterranean island

ABSTRACT Crete is a Mediterranean, karst-dominated island, characterized by long drought periods. The Karst-SWAT model, combined with 11 climate change scenarios, was run to assess climate change impacts on the island under two set-ups, both using the auto-irrigation function of the model: (1) with water drawn from the shallow or deep aquifer, and (2) with irrigated water derived from an unlimited outside source. The first set-up provided insight into the fluctuation of future irrigation needs, and when compared to the second set-up, enabled quantification of the future water deficit. The Water Exploitation Index was used to describe the spatial variability of future water stress on Crete. A decrease in both surface and karstic spring flows is foreseen, especially after 2060 (24.2 and 16.5%, respectively). Simulated irrigation water demand and water deficit show continuous increase throughout the projection period (2020–2098).

Utilizing SMAP Soil Moisture Data to Constrain Irrigation in the Community Land Model

AbstractIrrigation representation in land surface models has been advanced over the past decade, but the soil moisture (SM) data from SMAP satellite have not yet been utilized in large‐scale irrigation modeling. Here we investigate the potential of improving irrigation representation in the Community Land Model version‐4.5 (CLM4.5) by assimilating SMAP data. Simulations are conducted over the heavily irrigated central U.S. region. We find that constraining the target SM in CLM4.5 using SMAP data assimilation with 1‐D Kalman filter reduces the root‐mean‐square error of simulated irrigation water requirement by 50% on average (for Nebraska, Kansas, and Texas) and significantly improves irrigation simulations by reducing the bias in irrigation water requirement by up to 60%. An a priori bias correction of SMAP data further improves these results in some regions but incrementally. Data assimilation also enhances SM simulations in CLM4.5. These results could provide a basis for improved modeling of irrigation and land‐atmosphere interactions.

Agricultural water supply/demand changes under projected future climate change in the arid region of northwestern China

The water resources in the arid region of northwestern China, which are impacted by climate change, tend to be more unstable, and the environment and ecosystems will suffer from severe water shortage. In this paper, potential future climate trends were predicted based on CMIP5 simulations in this region. The water availability and agricultural water demand under future climate change scenarios were estimated. Impacted by increases in temperature, the irrigation water demand will increase by 4.27–6.15billionm3 in this region over the next 60years, compared to the demand of 32.75billionm3 during 1971–2000. However, the annual runoff will only increase by 4.8–8.5billionm3, which is equivalent to or even less than the increased irrigation water demand. In fact, the increased demand for industrial, domestic and ecological water were not considered here. Thus, the water supply/demand contradiction will result in more severe water shortages in the future. According to a comparison with simulated irrigation water demand under three adaptation strategy scenarios, we should take effective measures such as improving the efficiency of irrigation water utilization, reducing crop planting areas and adjusting crop planting structures to alleviate the impacts of future climate changes and human activities on the water supply and water use in this region.

Cadmium Uptake and Translocation of Tomato in Response to Simulated Irrigation Water Containing Elevated Concentrations of Cadmium and Zinc in Clayey Soil

Accumulation of metals in cultivated crops is considered one of the primary constraints to irrigated agriculture. A greenhouse pot experiment was carried out to study the effects of irrigation with elevated cadmium (Cd) and a combination of cadmium and zinc (Zn) levels on Cd uptake, translocation, and productivity of tomato (Solanum lycopersicum) plants. Tomato seedlings were grown in 3-kg pots irrigated for three months until maturity. Treatments were as follows: pots irrigated with fresh water containing Cd concentrations (0, 0.01, 0.04, 0.16, 0.64, 2.54 mg L−1), and pots irrigated with a combination of Cd + Zn concentrations (0 + 0, 0.01 + 2, 0.04 + 8, 0.16 + 32, 0.64 + 128, and 2.56 + 256 mg L−1). Cadmium and Zn concentration in soil and plant parts (root, shoot, and fruit) increased with increasing metal dose in irrigation water. Results also showed that Cd accumulation in the fruit was much lower than in the shoot indicating lower Cd transfer from soil to the fruit. Tomato biomass was not affected by treatments even at the highest metal dose. The uptake of Cd in tomato fruit ranged from 0.5 to 2.0 and from 0.3 to 1 mg kg−1, in single and combination treatments, respectively. Cadmium in fruit exceeded the permissible limit at 0.04 and 0.16 + 32 mg L−1 in Cd and Cd + Zn treatments, respectively. Therefore these levels could be considered as a threshold for tomato cultivation in clayey soil.

Effect of Incident Rainfall Redistribution by Maize Canopy on Soil Moisture at the Crop Row Scale

The optimization of irrigation use in agriculture is a key challenge to increase farm profitability and reduce its ecological footprint. To this context, an understanding of more efficient irrigation systems includes the assessment of water redistribution at the microscale. This study aimed to investigate rainfall interception by maize canopy and to model the soil water dynamics at row scale as a result of rain and sprinkler irrigation with HYDRUS 2D/3D. On average, 78% of rainfall below the maize canopy was intercepted by the leaves and transferred along the stem (stemflow), while only 22% reached the ground directly (throughfall). In addition, redistribution of the water with respect to the amount (both rain and irrigation) showed that the stemflow/throughfall ratio decreased logarithmically at increasing values of incident rainfall, suggesting the plant capacity to confine the water close to the roots and diminish water stress conditions. This was also underlined by higher soil moisture values observed in the row than in the inter-row at decreasing rainfall events. Modelled data highlighted different behavior in terms of soil water dynamics between simulated irrigation water distributions, although they did not show significant changes in terms of crop water use efficiency. These results were most likely affected by the soil type (silty-loam) where the experiment was conducted, as it had unfavorable physical conditions for the rapid vertical water movement that would have increased infiltration and drainage.

Simulation of a Right Abshar Irrigation Network and Its Cropping Pattern Using a System Dynamics Approach

AbstractUsing irrigation and drainage networks will lead to greater productivity and economic benefits. In this study, using a system dynamics approach, a computer model was developed that can estimate the crop yield of an irrigation network according to the quantity and quality of simulated irrigation water and to estimate the net profit of products. In order to calibrate and validate the model results, data collected from the research area of a right Abshar irrigation network was used. After statistical analysis and calculation of the root-mean-square error (RMSE), relative error, standard error, and correlation coefficient, the adjustment between the performance of measured and simulated network products was calculated. The value of these product indexes, according to the conditions on the network, were estimated as 209.98 kg/ha, 1.36%, 0.007, and 0.99, respectively. The results showed that the model in the simulated irrigation network, its cropping pattern, and the definition of other scenarios has a...

Modeling the impacts of increase in temperature on irrigation water requirements in Palakkad district: a case study in humid tropical Kerala

Rise in temperature is one of the predicted impacts of climate change with significant implications on water resources management. An attempt has been made to calculate the water requirement of crops in different agro-ecological zones of Palakkad district in humid tropical Kerala using the CROPWAT 8.0 model. Sensitivity analysis was done for a simulated rise in temperature from 0.5 to 3.0 °C keeping other parameters the same. The analysis showed that the total crop water requirement of all the major crops, like coconut, paddy and banana, increased with rising temperature thereby increasing the simulated irrigation water demand. The gross water demand inclusive of irrigation, domestic and industries will be 1,496 Mm3. The simulated gross water demand for an increase in temperature of 0.5, 1.0, 2.0 and 3.0 °C will be 1,523, 1,791, 1,822 and 1,853 Mm3, respectively. The maximum utilizable water resource available in the district is only 1,579 Mm3 and better water management, focusing particularly on improving the irrigation efficiency, has to be adopted to cater for the demands of the user sectors under changing climate scenario. A wide spectrum of climate change scenarios is also discussed in the paper along with guidelines for the future management of water resources.