Korea repeatedly experiences flash floods and droughts that cause traumatic environmental conditions with huge economic impact. Recently due to climate change, the frequency and magnitude of natural disasters associated with extreme hydrologic events increased rapidly in Korea. Floods caused the greatest damage among all natural disasters. To prevent this damage it is important to inform people about ongoing and upcoming flash flood events to avoid the loss of life and property. In this study hardware and software based smart technology is used to develop an early flood warning system for Mushim stream watershed to send to end users early flood warning messages about potentially impacted areas. Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) is the core of flood alert application provides the forecast with sufficient lead time and decides the threshold conditions of runoff/stage. Short range weather forecasts from Korea Meteorological Administration (KMA) at every three hours interval, are stored in hydro-meteorological database and fed in HEC-HMS for identification of flood risks. Server-Client based program used to visualize the real time flood condition and to deliver the early warning message. The findings of this study are expected to be used as basic data required for designing of flood mitigation measures at Mushim stream watershed to cope with the flash flood events in future. The flood hazard maps thus developed will be useful to policy-makers and responsible authorities, as well as to local residents in finding suitable measures for reducing flood risk in the study area

High spatial and temporal variation in precipitation in South Korea leads to an increase in the frequency and duration of drought. In this study, the spatial characteristics of temporal trends for precipitation and drought severity time series were analyzed at 55 stations across South Korea for the period 1980–2015. This study also reviewed the usefulness of different trend tests while addressing the issue of serial correlation, which has often received less attention in previous studies. Results showed that most significant trends in precipitation were detected along the south coast of South Korea, especially during winter, late spring and summer, whereas no significant trend was detected in annual precipitation. The Sen’s slope of the trends increased from January to August and decreased from August onward. Principal component analysis applied on Standardized Precipitation Index (SPI) at a 12-month time scale divides the whole of South Korea into four subregions with different temporal behaviors of drought severity. Moreover, drought severity showed a significant increasing trend, mainly on the northeast coast. Drought frequency analysis showed more frequent droughts in late winter, early spring and early autumn, with less frequent droughts in summer.

In South Korea, meteorological droughts are becoming frequently-occurring phenomena in different parts of the country, because precipitation varies significantly in both space and time. In this study, the quantiles of four identified homogeneous regions were estimated by incorporating major drought variables (e.g., duration and severity) based on the Standardized Precipitation Index (SPI). The regional frequency analysis of drought was performed by evaluating a variety of probability distributions and copulas, using graphical comparisons and goodness-of-fit test statistics. Results indicate that the Pearson type III (PE3) and Kappa marginal distributions, as well as Gaussian and Frank copulas, are better able to simulate the drought variables across the region. Bivariate stochastic simulation of selected copulas showed that the behavior of simulated data may change when the degree of association (e.g., Kendall’s τ) between the drought variables was considered. Results showed that the south-west coast and east coastal areas are under high drought risk, and inland mid-latitude areas (surrounding areas of Yeongju station) and northwest parts are under low drought risk. The joint distributions were used to compute conditional probabilities, as well as primary, secondary, and conditional return periods, which can be useful for designing and managing water demand and the supply system on a regional scale.

In this study, the performances of four satellite-based precipitation products (IMERG-V06 Final-Run, TRMM-3B42V7, SM2Rain-ASCAT, and PERSIANN-CDR) were assessed with reference to the measurements of in-situ gauges at daily, monthly, seasonal, and annual scales from 2010 to 2017, over the Hindu Kush Mountains of Pakistan. The products were evaluated over the entire domain and at point-to-pixel scales. Different evaluation indices (Correlation Coefficient (CC), Root Mean Square Error (RMSE), Bias, and relative Bias (rBias)) and categorical indices (False Alarm Ration (FAR), Critical Success Index (CSI), Success Ratio (SR), and Probability of Detection (POD)) were used to assess the performances of the products considered in this study. Our results indicated the following. (1) IMERG-V06 and PERSIANN capably tracked the spatio-temporal variation of precipitation over the studied region. (2) All satellite-based products were in better agreement with the reference data on the monthly scales than on daily time scales. (3) On seasonal scale, the precipitation detection skills of IMERG-V06 and PERSIANN-CDR were better than those of SM2Rain-ASCAT and TRMM-3B42V7. In all seasons, overall performance of IMERG-V06 and PERSIANN-CDR was better than TRMM-3B42V7 and SM2Rain-ASCAT. (4) However, all products were uncertain in detecting light and moderate precipitation events. Consequently, we recommend the use of IMERG-V06 and PERSIANN-CDR products for subsequent hydro-meteorological studies in the Hindu Kush range.

Pakistan faces water scarcity and high operational costs for traditional irrigation systems, hindering agricultural productivity. Solar-powered irrigation systems (SPIS) can potentially provide a sustainable and affordable solution, but face technical, financial and policy barriers to adoption. A comprehensive study is needed to examine feasibility and identify barriers. Therefore, a comprehensive review study is conducted to identify the potential for solar irrigation, key issues and challenges related to its implementation in Pakistan. The analysis is based on published studies, technical reports and a survey of solar-powered drip irrigation systems. The use of SPIS in Pakistan is becoming a cost-effective and sustainable option for irrigation, particularly in remote and off-grid areas. However, these systems also have their challenges, such as high initial costs, maintenance and repairs, limited access to spare parts, lack of government policies and regulations, lack of technical expertise, lack of financing options and social acceptance. The most pressing issue is the risk of groundwater exploitation by using SPIS. Based on the analysis of the energy and water situation in Pakistan, it is important to sustainably use both solar energy and groundwater resources, through the implementation of effective management strategies and policies. With the right policies and investment in research and development of SPIS and groundwater, farmers can benefit by increasing crop yields, conserving water resources, reducing the cost of energy, increasing productivity and improving the standard of living and access to electricity in remote and off-grid areas. It is recommended that the adoption of solar energy be promoted to run high efficiency irrigation systems (HEIS) with urgent capacity improvement among farmers, advisors and system installers to sustainably manage water resources in SPIS. This would not only help to reduce the consumption of fossil fuels and associated environmental impacts, but also increase farmers’ income and reduce their operational costs. Moreover, the use of SPIS can improve crop yields, leading to food security and poverty reduction. Thus, the government and policymakers should consider implementing policies and incentives to encourage the large-scale adoption of solar energy in the agricultural sector.