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The use of advanced resource conservation techniques is the need of time for higher crop production under the challenges of water scarcity and climate change. The present study was planned (1) to evaluate different plant spacing of corn, sown under raised bed planting (RBP) for higher productivity, (2) calibrate APSIM model for experimental treatments and (3) simulate future (2022–2100) crop response under different scenarios of climate change. The two-year research experiments were conducted on corn with four different plant spacings (S1:15 cm, S2:17.5 cm, S3:20 cm and S4:22.5 cm) under RBP. The crop response was evaluated in terms of leaf area index (LAI), plant height, flowering date, grains per cob, grain yield, biomass yield, harvest index (HI) and water productivity. The S1 treatment produced the highest productivity in terms of grain yield (7.16 Mg/hm2), biomass yield (16.57 Mg/hm2), HI (0.44) and water productivity (1.33 kg/m3). APSIM model was calibrated and its ability to simulate crop response during validation was confirmed from the values of RMSE, NRMSE, R2, CRM and NSE as 0.4, 0.21, 0.83, 0.04 and 0.68 for grain yield. The RMSE and NRMSE were 0.79 and 0.14 for biomass yield. The value of R2 ranged from 0.69 to 0.85, CRM from –0.03 to 0.005, NSE from 0.69 to 0.86 for biomass yield, plant height and LAI. During scenario simulations, the model run was performed against different plant spacing for optimization and results revealed that 10 cm plant spacing produced highest corn yield and growth parameters. Further simulations (2022–2100) were performed using climatic data, acquired from different general circulation model (GCMs) for two rcps (4.5 and 8.5) and results revealed the reduction in grain and biomass yields by 8–14 % and 10–28 %, respectively against different data sources (GCMs). Optimized plant spacing (10 cm) under RBP produced 35.5 % more grain yield and 29.3 % more biomass yield than that under control treatment (ridge-furrow system). Based on the research findings, it is recommended that conservation technique like RBP needs to be adopted in semi-arid regions to mitigate the impact of climate change in terms of future temperature rise for better corn production.

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

Climate change poses emerging threats to wheat growth in coming future. These threats need to be explored to ensure sustainable wheat production. To do this, the SALTMED model was calibrated using data from experiments conducted on different levels of irrigation and nitrogen doses. The performance of the SALTMED model was assessed based on values of the root mean square error (RMSE), normalized root mean square error (NRMSE), coefficient of determination (R2) and coefficient of residual mass (CRM) that ranged from 0.23–1.82, 0.09–0.17, 0.91–0.93 and −0.01–0.02, respectively for calibration and 0.31–1.89, 0.11–0.31, 0.87–0.90 and −0.02–0.01, respectively for validation. Projections for future climate scenarios for wheat growth indicated that by the end of the century, sowing dates advanced by nine days under the RCP4.5 scenario and eleven days under the RCP8.5 scenario, while harvesting dates shifted earlier by twenty-four days under RCP4.5 and twenty-eight days under RCP8.5. Consequently, the overall crop duration was shortened by fifteen days under RCP4.5 and eighteen days under RCP8.5. Further simulations revealed that the wheat yield was reduced by 14.2% under RCP4.5 and 21.0% under RCP8.5; the dry matter was reduced by 14.9% under RCP4.5 and 23.3% under RCP8.5; the irrigation amount was expected to increase by 14.9% under RCP4.5 and 18.0% under RCP8.5; and water productivity was expected to be reduced by 25.3% under RCP4.5 and 33.0% under RCP8.5 until the end of century. The hypothetical scenarios showed that adding an extra 20–40% more nitrogen can enhance wheat yield and dry matter by 10.2–23.0% and 11.5–24.6%, respectively, under RCP4.5, and by 12.0–23.4% and 12.9–29.6%, respectively, under RCP8.5. This study offers valuable insights into the effects of climate change on future wheat production so that effective contingency plans could be made by policymakers and adopted by stakeholders for higher wheat productivity.

The non-judicious use of water at the farm level in traditional irrigation application methods is a present-day concern across the world that can be resolved by enhancing application efficiency through the adoption of advanced irrigation techniques. Sprinkler irrigation is a method that has high application efficiency, which can be further increased when coupled with automation toward precision irrigation. The objectives of this review are to summarize the main aspects of sprinkler and precision irrigation and their development, scope, and future prospects specifically in Asian countries. In this paper, a modified methodology, inspired by PRISMA guidelines, was used to explore the available literature to summarize the existing knowledge in the field. Regarding the technological aspects of the analyzed works, it became evident that sprinkler systems are an efficient method to not only irrigate crops (with 39% water saving) but also for the application of fertilizers with higher efficiency (>35%) and water productivity (>14.1%) compared with gravity irrigation systems. Moreover, this paper highlights the prominent features of precision irrigation for maximizing agricultural productivity. The use of sprinkler irrigation with precision applications using automation with a sensor-based mechanism for field data collection, data transformation, data analysis, and operation of IoT-based automatic solenoid valves can save 20–30% more irrigation water and increase crop yield by 20–27%. An analytical understanding and knowledge of the field were used to draw conclusions that are thought-provoking for scientists, researchers, and other stakeholders.

Abstract Pakistan experiences extreme flood events almost every year during the monsoon season. Recently, flood events have become more disastrous as their frequency and magnitude have increased due to climate change. This situation is further worsened due to the limited capacity of existing water reservoirs and their ability to absorb and mitigate peak floods. Thus, the simulation of stream flows using projected data from climate models is essential to assess flood events and proper water resource management in the country. This study investigates the future floods (in near future and far future periods) using the integrated flood analysis system (IFAS) model under the RCP2.6, RCP4.5, and RCP8.5 climate change scenarios. Downscaled and bias corrected climatic data of six general circulation models and their ensemble were used in this study. The IFAS model simulated the stream flow efficiently (R2 = 0.86–0.93 and Nash–Sutcliffe efficiency = 0.72–0.92) in the Jhelum River basin (JRB), Kabul River basin (KRB), and upper Indus River basin (UIRB) during the calibration and validation periods. The simulation results of the model showed significant impact of projected climate change on stream flows that will cause the mean monthly stream flow in the JRB to be lower, while that of the KRB and UIRB to be higher than that of the historical period. The highest flow months are expected to shift from May–June (Jhelum basin) and June–July (Kabul basin) to April–May with no changes in the UIRB. Higher frequencies of low to medium floods are projected in the KRB and UIRB, while the JRB expects fewer flood events. Based on the results from the IFAS model, it is concluded that stream flow in the study area will increase with several flood events.

Water plays a crucial role in better agricultural production. The situation of irrigation water in Pakistan is getting worse day by day. New sowing techniques for high-value agriculture are the only solution to increasing water and crop productivity. Drip irrigation coupled with mulch in tunnel farming can be an effective tool for better agricultural production. Therefore, this study was designed to check the impact of different mulch materials coupled with various irrigation schedules on cucumber yield and its root zone behavior. Three types of mulch, i.e., black, transparent, and wheat straw, each under two different levels of deficit irrigation (DI) of 20% DI and 40% DI, were compared with farmer practice as a control. The experiment was conducted at a farmer’s field and laid out under a randomized complete block design. The effect of treatments was checked on the number of leaves per plant, plant height, number of fruits per plant, fruit weight per plant, and crop yield. Moreover, the effect of treatments was checked on the crop root zone. The Hydrus-1D model was calibrated to successfully simulate soil moisture in the root zone. The study’s results revealed that among all treatments, the total yield of the cucumber was higher under 20% DI than 40%. The treatment T3 (transparent mulch + 20% DI) had a maximum yield of 47.31 tons/ha, whereas the minimum yield of 31.86 tons/ha was obtained under control. There was little difference between the yield of black plastic mulch and wheat straw mulch. Maximum root length was found in the case of black mulch with 20% DI (86.9 cm), and the maximum diameter of the root zone canopy was observed under wheat straw mulch. Hydrus-1D proved its ability and was recommended for simulating root zone moisture, with the lowest value of R2 = 0.894. It was concluded that cucumber production with 20% DI is viable for drip irrigation with mulch applications.

Agriculture is the major economic sector in Asian countries and the majority of their population depends on it. In addition to the largest irrigation system in the Indus basin, Pakistan is suffering from water shortages that are affecting the overall crop production of the country. Different resource conservation technologies (RCTs) such as precision land leveling (PLL), raised bed planting (RBP), and different high-efficiency irrigation systems (HEISs) can be opted for better water productivity. In this study, the potential of these RCTs has been explored to enhance production and save irrigation water through their sustainable adoption. Based on studies by different researchers, water savings up to 47% and yield increases up to 35% have been reported under PLL, while water savings up to 50% and about 10–33% yield increases were observed under RBP. Similarly, under different HEISs, water savings up to 80% and yield increases up to 53% have been reported compared with crops sown under conventional farming. Based on the findings of the researchers regarding RCTs, these have been proved as progressive sowing techniques for better productivity under the limited available water scenario. The detailed review in this paper concludes that RCTs resulting in the improvement of gravity irrigation methods, viz., PLL and RBP, have a great potential of adoption and water productivity improvement at the regional scale in developing countries such as Pakistan, while high-cost HEISs can also be promoted at limited scale among progressive farmers for high-value agriculture.

Water resources are highly dependent on climatic variations. The quantification of climate change impacts on surface water availability is critical for agriculture production and flood management. The current study focuses on the projected streamflow variations in the transboundary Mangla Dam watershed. Precipitation and temperature changes combined with future water assessment in the watershed are projected by applying multiple downscaling techniques for three periods (2021–2039, 2040–2069, and 2070–2099). Streamflows are simulated by using the Soil and Water Assessment Tool (SWAT) for the outputs of five global circulation models (GCMs) and their ensembles under two representative concentration pathways (RCPs). Spatial and temporal changes in defined future flow indexes, such as base streamflow, average flow, and high streamflow have been investigated in this study. Results depicted an overall increase in average annual flows under RCP 4.5 and RCP 8.5 up until 2099. The maximum values of low flow, median flow, and high flows under RCP 4.5 were found to be 55.96 m3/s, 856.94 m3/s, and 7506.2 m3/s and under RCP 8.5, 63.29 m3/s, 945.26 m3/s, 7569.8 m3/s, respectively, for these ensembles GCMs till 2099. Under RCP 4.5, the maximum increases in maximum temperature (Tmax), minimum temperature (Tmin), precipitation (Pr), and average annual streamflow were estimated as 5.3 °C, 2.0 °C, 128.4%, and 155.52%, respectively, up until 2099. In the case of RCP 8.5, the maximum increase in these hydro-metrological variables was up to 8.9 °C, 8.2 °C, 180.3%, and 181.56%, respectively, up until 2099. The increases in Tmax, Tmin, and Pr using ensemble GCMs under RCP 4.5 were found to be 1.95 °C, 1.68 °C and 93.28% (2021–2039), 1.84 °C, 1.34 °C, and 75.88%(2040–2069), 1.57 °C, 1.27 °C and 72.7% (2070–2099), respectively. Under RCP 8.5, the projected increases in Tmax, Tmin, and Pr using ensemble GCMs were found as 2.26 °C, 2.23 °C and 78.65% (2021–2039), 2.73 °C, 2.53 °C, and 83.79% (2040–2069), 2.80 °C, 2.63 °C and 67.89% (2070–2099), respectively. Three seasons (spring, winter, and autumn) showed a remarkable increase in streamflow, while the summer season showed a decrease in inflows. Based on modeling results, it is expected that the Mangla Watershed will experience more frequent extreme flow events in the future, due to climate change. These results indicate that the study of climate change’s impact on the water resources under a suitable downscaling technique is imperative for proper planning and management of the water resources.

The source region of the Indus River (SRIR), which is located in the Hindukush, Karakoram and Himalayan (HKH) mountainous range and on the Third Pole (TP), is very sensitive to climate change, especially precipitation changes, because of its multifarious orography and fragile ecosystem. Climate changes in the SRIR also have important impacts on social and economic development, as well as on the ecosystems of the downstream irrigation areas in Pakistan. This paper investigates the changes in precipitation characteristics by dividing the daily precipitation rate into different classes, such as light (0−10 mm), moderate (10.1−25 mm) and heavy precipitation (>25 mm). Daily precipitation data from gauging and non-gauging stations from 1961−2015 are used. The results of the analysis of the annual precipitation and rainy day trends show significant (p < 0.05) increases and decreases, respectively, while light and heavy precipitation show significant decreasing and increasing trends, respectively. The analysis of the precipitation characteristics shows that light precipitation has the highest number of rainy days compared to moderate or heavy precipitation. The analysis of the seasonal precipitation trends shows that only 18 stations have significant increasing trends in winter precipitation, while 27 stations have significant increasing trends in summer precipitation. Both short and long droughts exhibit increasing trends, which indicates that the Indus Basin will suffer from water shortages for agriculture. The results of this study could help policymakers cope with floods and droughts and sustain eco-environmental resources in the study area.