Research

17 pages, 3996 KiB

Open AccessFeature PaperArticle

Investigation of Irrigation Water Requirements for Major Crops Using CROPWAT Model Based on Climate Data

by Ghulam Shabir Solangi, Sabab Ali Shah, Raied Saad Alharbi, Sallahuddin Panhwar, Hareef Ahmed Keerio, Tae-Woong Kim, Junaid Ahmed Memon and Ali Dost Bughio

Water 2022, 14(16), 2578; https://doi.org/10.3390/w14162578 - 21 Aug 2022

Cited by 10 | Viewed by 5528

Abstract

Water is one of the most important natural resources and is widely used around the globe for various purposes. In fact, the agricultural sector consumes 70% of the world’s accessible water, of which about 60% is wasted. Thus, it needs to be managed [...] Read more.

Water is one of the most important natural resources and is widely used around the globe for various purposes. In fact, the agricultural sector consumes 70% of the world’s accessible water, of which about 60% is wasted. Thus, it needs to be managed scientifically and efficiently to maximize food production to meet the requirements of an ever-increasing population. There is a lack of information on water requirements of crops and irrigation scheduling concerning the Shaheed Benazirabad district, Pakistan. Thus, the present study was conducted to determine the irrigation water requirements (IWR) and irrigation scheduling for the major crops in the Shaheed Benazirabad district, Sindh, Pakistan, using agro-climatic data and the CROPWAT model. Agro-climatic data such as rainfall, maximum and minimum temperature, sunshine hours, humidity, and wind speed were obtained from the NASA website, CLIMWAT 2.0, and world weather However, data about studied crops and soils were obtained from FAO (Food and Agriculture Organization). Analysis revealed that the IWRs per irrigation round for the four major crops—sugarcane, banana, cotton, and wheat—were as 3108.0 mm, 1768.5 mm, 1655.7 mm, and 402.5 mm, respectively. It was observed the IWRs are more sensitive in the hot season because of high temperatures and low relative humidity, and vice versa in the cold season. The use of scientific tools such as CROPWAT is recommended to assess IWRs with a high degree of accuracy and to compute irrigation scheduling. Accordingly, the study results will be helpful for improving food production and supervision of water resources. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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18 pages, 3394 KiB

Open AccessArticle

Optimizing Parameters for the Downscaling of Daily Precipitation in Normal and Drought Periods in South Korea

by Seon-Ho Kim, Jeong-Bae Kim and Deg-Hyo Bae

Water 2022, 14(7), 1108; https://doi.org/10.3390/w14071108 - 30 Mar 2022

Cited by 2 | Viewed by 1545

Abstract

One important factor that affects the performance of statistical downscaling methods is the selection of appropriate parameters. However, no research on the optimization of downscaling parameters has been conducted in South Korea to date, and existing parameter selection methods are dependent on studies [...] Read more.

One important factor that affects the performance of statistical downscaling methods is the selection of appropriate parameters. However, no research on the optimization of downscaling parameters has been conducted in South Korea to date, and existing parameter selection methods are dependent on studies conducted in other regions. Moreover, several large-scale predictors have been used to predict abnormal phenomena such as droughts, but in the field of downscaling, parameter optimization methods that are suitable for drought conditions have not yet been developed. In this study, by using the K-nearest analog methodology, suitable daily precipitation downscaling parameters for normal and drought periods were derived. The predictor variables, predictor domain, analog date size, time dependence parameters, and parameter sensitivity values that are representative of South Korea were presented quantitatively. The predictor variables, predictor domain, and analog date size were sensitive to the downscaling performance in that order, but the time dependency did not affect the downscaling process. Regarding calibration, the downscaling results obtained based on the drought parameters returned smaller root mean square errors of 1.3–28.4% at approximately 70% of the stations compared to those of the results derived based on normal parameters, confirming that drought parameter-based downscaling methods are reasonable. However, as a result of the validation process, the drought parameter stability was lower than the normal parameter stability. In the future, further studies are needed to improve the stability of drought parameters. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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14 pages, 20335 KiB

Open AccessFeature PaperArticle

Estimating Optimal Design Frequency and Future Hydrological Risk in Local River Basins According to RCP Scenarios

by Jae-Hee Ryu, Ji-Eun Kim, Jin-Young Lee, Hyun-Han Kwon and Tae-Woong Kim

Water 2022, 14(6), 945; https://doi.org/10.3390/w14060945 - 17 Mar 2022

Cited by 3 | Viewed by 1538

Abstract

In South Korea, flood damage mainly occurs around rivers; thus, it is necessary to determine the optimal design frequency for river basins to prevent flood damage. However, there are not enough studies showing the effect of climate change on hydrologic design frequency. Therefore, [...] Read more.

In South Korea, flood damage mainly occurs around rivers; thus, it is necessary to determine the optimal design frequency for river basins to prevent flood damage. However, there are not enough studies showing the effect of climate change on hydrologic design frequency. Therefore, to estimate the optimal design frequency according to future climate change scenarios, this study examined urban flooding area and extreme rainfall frequency that can change in the future. After estimating the optimal design frequency, hydrological risks of 413 local river basins were evaluated according to Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 after regenerating daily rainfalls from the HadGEM2-ES model into hourly rainfalls using the Poisson cluster. For the RCP 4.5, hydrological risks increased relative to the established design frequency by 3.13% on average. For the RCP 8.5, hydrological risks increased by 2.80% on average. The hydrological risks increased by 4.58% in the P2(2040–2069) period for the RCP 4.5, and by 4.39% in the P1 (2021–2039) period for the RCP 8.5. These results suggest that the hydrologic design frequency in the future will likely decrease, and the safety of river basins will also decrease. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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14 pages, 3566 KiB

Open AccessArticle

Investigation of the Effects of Climate Variability, Anthropogenic Activities, and Climate Change on Streamflow Using Multi-Model Ensembles

by Sabab Ali Shah, Muhammad Jehanzaib, Jiyoung Yoo, Seungho Hong and Tae-Woong Kim

Water 2022, 14(4), 512; https://doi.org/10.3390/w14040512 - 09 Feb 2022

Cited by 12 | Viewed by 2464

Abstract

Streamflow is a very important component of the hydrological cycle, and variation in the streamflow can be an indication of hydrological disaster. Thus, the accurate quantification of streamflow variation is a core concern in water resources engineering. In this study, we evaluated the [...] Read more.

Streamflow is a very important component of the hydrological cycle, and variation in the streamflow can be an indication of hydrological disaster. Thus, the accurate quantification of streamflow variation is a core concern in water resources engineering. In this study, we evaluated the factors influencing streamflow and decomposed their effects in three large rivers: the Buk Han River (BHR), the Nam Han River (NHR), and the Lower Han River (LHB). The Pettit test was used to investigate breakpoints in conjunction with the climate elasticity approach and decomposition framework to quantify and decompose the effects of climate variability and anthropogenic activity. The abrupt breakpoints in the streamflow and precipitation data were detected in 1997 and 1995. Considering these breakpoints, we divided the time series into two periods: the baseline period and the post-baseline period. Climate elasticity approaches were used to quantify the effects of climate variability and anthropogenic activity during the baseline period, post-baseline period, and future periods (2031–2060 and 2071–2100) under the Representative Concentration Pathways’ 4.5 and 8.5 scenarios. The results revealed that climate variability was the leading cause of alteration in the streamflow in the BHR and NHR, accounting for 76.52% to 80.51% of the total change, respectively. Meanwhile, the LHR remained more sensitive to anthropogenic activity, which accounted for 56.42% of the total variation in streamflow. Future climate change also showed an increase in precipitation and temperature in both scenarios, especially during the far-future period (2071–2100). This variation in the climatic factor was shown to affect the future streamflow by 22.14% to 27.32%. These findings can play a very important role in future planning for large river basins, considering the impacts of increasing anthropogenic activity and climate change to reduce the risks of hydrological hazards. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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18 pages, 3734 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Machine Learning Techniques for Hydrological Drought Modeling: A Case Study of the Wadi Ouahrane Basin in Algeria

by Mohammed Achite, Muhammad Jehanzaib, Nehal Elshaboury and Tae-Woong Kim

Water 2022, 14(3), 431; https://doi.org/10.3390/w14030431 - 30 Jan 2022

Cited by 28 | Viewed by 5082

Abstract

Forecasting meteorological and hydrological drought using standardized metrics of rainfall and runoff (SPI/SRI) is critical for the long-term planning and management of water resources at the global and regional levels. In this study, various machine learning (ML) techniques including four methods (i.e., ANN, [...] Read more.

Forecasting meteorological and hydrological drought using standardized metrics of rainfall and runoff (SPI/SRI) is critical for the long-term planning and management of water resources at the global and regional levels. In this study, various machine learning (ML) techniques including four methods (i.e., ANN, ANFIS, SVM, and DT) were utilized to construct hydrological drought forecasting models in the Wadi Ouahrane basin in the northern part of Algeria. The performance of ML models was assessed using evaluation criteria, including RMSE, MAE, NSE, and R². The results showed that all the ML models accurately predicted hydrological drought, while the SVM model outperformed the other ML models, with the average RMSE = 0.28, MAE = 0.19, NSE = 0.86, and R² = 0.90. The coefficient of determination of SVM was 0.95 for predicting SRI at the 12-months timescale; as the timescale moves from higher to lower (12 months to 3 months), R² starts decreasing. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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20 pages, 6250 KiB

Open AccessArticle

Integrated Quality Control Process for Hydrological Database: A Case Study of Daecheong Dam Basin in South Korea

by Gimoon Jeong, Do-Guen Yoo, Tae-Woong Kim, Jin-Young Lee, Joon-Woo Noh and Doosun Kang

Water 2021, 13(20), 2820; https://doi.org/10.3390/w13202820 - 11 Oct 2021

Viewed by 1892

Abstract

In our intelligent society, water resources are being managed using vast amounts of hydrological data collected through telemetric devices. Recently, advanced data quality control technologies for data refinement based on hydrological observation history, such as big data and artificial intelligence, have been studied. [...] Read more.

In our intelligent society, water resources are being managed using vast amounts of hydrological data collected through telemetric devices. Recently, advanced data quality control technologies for data refinement based on hydrological observation history, such as big data and artificial intelligence, have been studied. However, these are impractical due to insufficient verification and implementation periods. In this study, a process to accurately identify missing and false-reading data was developed to efficiently validate hydrological data by combining various conventional validation methods. Here, false-reading data were reclassified into suspected and confirmed groups by combining the results of individual validation methods. Furthermore, an integrated quality control process that links data validation and reconstruction was developed. In particular, an iterative quality control feedback process was proposed to achieve highly reliable data quality, which was applied to precipitation and water level stations in the Daecheong Dam Basin, South Korea. The case study revealed that the proposed approach can improve the quality control procedure of hydrological database and possibly be implemented in practice. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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17 pages, 5547 KiB

Open AccessArticle

Evaluation of Drought Resilience Reflecting Regional Characteristics: Focused on 160 Local Governments in Korea

by Chan-Wook Lee and Do-Guen Yoo

Water 2021, 13(13), 1873; https://doi.org/10.3390/w13131873 - 05 Jul 2021

Cited by 2 | Viewed by 2517

Abstract

It is critical to prepare appropriate responses and countermeasures against droughts caused by a complex hazard process as the range of its damage and duration are very large. In this study, 160 local governments in Korea evaluated drought resilience. A total of 18 [...] Read more.

It is critical to prepare appropriate responses and countermeasures against droughts caused by a complex hazard process as the range of its damage and duration are very large. In this study, 160 local governments in Korea evaluated drought resilience. A total of 18 qualitative and quantitative drought recovery indicators were selected to collect and analyze data from each region. Comparative analysis of indicators through regional drought assessment was conducted to derive results and present directions for enhancing resilience. Lastly, a resilience curve of drought that can utilize the results of the evaluation was suggested and applied to the actual region, and the results were analyzed. The proposed method can be expected to be used as a basic and essential resources to prepare various local government measures against drought. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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14 pages, 11432 KiB

Open AccessArticle

Evaluating the Hydrologic Risk of n-Year Floods According to RCP Scenarios

by Jin-Young Lee, Ho-Jun Son, Dongwook Kim, Jae-Hee Ryu and Tae-Woong Kim

Water 2021, 13(13), 1805; https://doi.org/10.3390/w13131805 - 29 Jun 2021

Cited by 4 | Viewed by 2210

Abstract

Recent climate change has brought about irregular rainfall patterns along with an increased frequency of heavy rainfall, and flood damage in Korea is increasing accordingly. The increased rainfall amount and intensity during the rainy season lead to flood damage on a massive scale [...] Read more.

Recent climate change has brought about irregular rainfall patterns along with an increased frequency of heavy rainfall, and flood damage in Korea is increasing accordingly. The increased rainfall amount and intensity during the rainy season lead to flood damage on a massive scale every year in Korea. In order to reduce such flood damage and secure the stability of hydraulic structures, evaluation of hydrologic risk corresponding to design floods is necessary. As Korea’s current climate change scenarios are generally applied to mid-sized watersheds, there is no practical application method to calculate the hydrologic risk of local floods corresponding to various future climate change scenarios. Using the design flood prediction model, this study evaluated the hydrologic risks of n-year floods according to 13 climate change scenarios. The representative concentration pathway (RCP) 8.5 scenario resulted in the 100-year floods increasing 134.56% on average, and 132.30% in the Han River, 132.81% in the Nakdong River, 142.42% in the Gum River, and 135.47% in the Seomjin-Youngsan River basin, compared with the RCP 4.5. The 100-year floods at the end of the 21st century increased by +3% and +13% according to the RCP 4.5 and 8.5, respectively. The corresponding hydrologic flood risk increased by 0.53% and 8.68% on average according to the RCP 4.5 and RCP 8.5, respectively, compared with the current level of hydrologic risk of a 100-year flood. Full article

(This article belongs to the Special Issue Assessing and Managing Risk of Flood and Drought in a Changing World)

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