Hydro-Meteorological Trends in Southwest Coastal Bangladesh: Perspectives of Climate Change and Human Interventions

The southwest coastal region of Bangladesh, being under tidal influence and dependent on sweet water supplies from upstream, has a unique brackish water ecosystem. The region, having vast low-lying areas enclosed by man-made polders, is considered to be highly vulnerable to climate change induced hazards. In this study, linear trends in hydro-climatic variables, such as temperature, rainfall, sunshine, humidity, sweet water inflow and tidal water level in the region are assessed using secondary data and following both parametric and nonparametric statistical techniques. Correlation between the sweet water flow from the Gorai River, a major distributary of the Ganges River, and the salinity level in the Rupsa-Pasur River near Khulna, a southern metropolis, is also investigated. The results reveal that the temperature in the Khulna region is increasing at a significant rate, particularly in recent years. The number of extremely cold nights is decreasing and the heat index is increasing. The sunshine duration has a decreasing trend and the humidity has an increasing trend. Rainfall is increasing in terms of both magnitude and number of rainy days. However, the annual maximum rainfall and the number of days with high intensity rainfall have remained almost static. The annual maximum tidal high water level is increasing and the annual minimum low water level is decreasing at a rate of 7 - 18 mm and 4 - 8 mm per year, respectively. There is a negative correlation between the Gorai flow and the river water salinity around Khulna. Dredging of the Gorai during 1998-2001 resulted in an improvement of the salinity situation in the Khulna region. The variation in water salinity, tidal water level and sweet water flows in different time periods indicates that the human interventions through upstream diversion and coastal polders have contributed more in hydro-morphological changes in the southwest than the climate change. However, there are some evidences of climate change in the meteorological variables at Khulna.

An Operational Hydro-Meteorological Chain to Evaluate the Uncertainty in Runoff Forecasting over the Verbano Basin

The development and implementation of a real-time flood forecasting system with a hydro-meteorological operational alert procedure during the MAP-D-PHASE Project is described in this paper. This chain includes both probabilistic and deterministic forecasts. The hydrological model used to generate the runoff simulations is the rainfall-runoff distributed FEST-WB model, developed at Politecnico di Milano. The observed data to run the control simulations were supplied by ARPA-Piemonte. The analysis is focused on Maggiore Lake basin, an Alpine basin between North-West of Italy and Southern Switzerland. Two hindcasts during the D-PHASE period are discussed in order to evaluate certain effects regarding discharge forecasts due to hydro-meteorological sources of uncertainties. In particular, in the June convective event it is analysed how the effect of meteorological model spatial resolution can influence the discharge forecasts over mountain basins, while in the November stratiform event how the effect of the initial conditions of soil moisture can modify meteorological warnings. The study shows how the introduction of alert codes appears to be useful for decision makers to give them a spread of forecasted QDFs with the probability of event occurrence, but also how alert warnings issued on the basis of forecasted precipitation only are not always reliable.

Forecast future disasters using hydro-meteorological datasets in the Yamuna river basin,Western Himalaya:Using Markov Chain and LSTM approaches

This research aim to evaluate hydro-meteorological data from the Yamuna River Basin,Uttarakhand,India,utilizing Extreme Value Distribution of Frequency Analysis and the Markov Chain Approach.This method assesses persistence and allows for combinatorial probability estimations such as initial and transitional probabilities.The hydrologic data was generated(in-situ)and received from Uttarakhand Jal Vidut Nigam Limited(UJVNL),and meteorological data was acquired from NASA’s archives MERRA-2 product.A total of sixteen years(2005-2020)of data was used to foresee daily Precipitation from 2020 to 2022.MERRA-2 products are utilized as observed and forecast values for daily Precipitation throughout the monsoon season,which runs from July to September.Markov Chain and Long Short-Term Memory(LSTM)findings for 2020,2021,and 2022 were observed,and anticipated values for daily rainfall during the monsoon season between July and September.According to test findings,the artificial intelligence technique cannot anticipate future regional meteorological formations;the correlation coefficient R^(2) is around 0.12.According to the randomly verified precipitation data findings,the Markov Chain model has a success rate of 79.17 percent.The results suggest that extended return periods should be a warning sign for drought and flood risk in the Himalayan region.This study gives a better knowledge of the water budget,climate change variability,and impact of global warming,ultimately leading to improved water resource management and better emergency planning to the establishment of the Early Warning System(EWS)for extreme occurrences such as cloudbursts,flash floods,landslides hazards in the complex Himalayan region.

Land Response to Atmosphere at Different Resolutions in the Common Land Model over East Asia

Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface mod- els are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model （CLM） was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System （KLDAS）, and Global Land Data Assimilation System （GLDAS）, at point and regional scales, separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r = 0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia.

Comparative study of probable maximum precipitation and isohyetal maps for mountainous regions, Pakistan

Probable maximum precipitation(PMP) is widely used by hydrologists for appraisal of probable maximum flood(PMF)used for soil and water conservation structures, and design of dam spillways. A number of methods such as empirical, statistical and dynamic are used to estimate PMP, the most favored being statistical and hydro-meteorological. In this paper,PMP estimation in mountainous regions of Pakistan is studied using statistical as well as physically based hydro-meteorological approaches. Daily precipitation, dew point, wind speed and temperature data is processed to estimate PMP for a one-day duration. Maximum precipitation for different return periods is estimated by using statistical approaches such as Gumble and Log-Pearson type-III(LP-III) distribution. Goodness of fit(GOF) test, chi-square test, correlation coefficient and coefficient of determination were applied to Gumble and LP-III distributions. Results reveal that among statistical approaches, Gumble distribution performed the best result compared to LP-III distribution. Isohyetal maps of the study area at different return periods are produced by using the GIS tool, and PMP in mountainous regions varies from 150 to 320 mm at an average value of 230.83 mm. The ratio of PMP for one-day duration to highest observed rainfall(HOR) varied from 1.08 to 1.29 with an average value of 1.18. An appropriate frequency factor(K_m) is very important which is a function of mean for observed precipitation and PMP for 1-day duration, and K_m values varies from 2.54 to 4.68. The coefficient of variability(C_v) varies from minimum value of 28% to maximum value of 43.35%. It was concluded that the statistical approach gives higher results compared to moisture maximization(MM) approach. In the hydro-meteorological approach, moisture maximization(MM) and wind moisture maximization(WMM) techniques were applied and it was concluded that wind moisture maximization approach gives higher results of PMP as compared to moisture maximization approach as well as for Hershfield technique. Therefore, it is suggested that MM approach is the most favored in the study area for PMP estimation, which leads to acceptable results, compared to WMM and statistical approaches.

Review of the development of hydrological data quality control in Typhoon Committee Members

Nowadays,with the continual development of the science and technology applied in data observation,monitoring and collection,human has more and more means and channels to obtain various data,consequently,the amount of collected and stored data is also getting bigger and bigger.In recent years,hydro-meteorological data have multiplied in some Typhoon Committee(TC)Members.Data-based advanced technology ap-plications in TC,such as application of Artificial Intelligent(AI)and impact-based typhoon disaster forecasting and early warning,has emerged one after another.A consistent and integrated data quality management system is crucial for ensuring accurate hydrological and meteorological analysis and prediction.Considering the importance and urgent necessary,TC working group on hydrology(WGH)conducted a cooperation project on data quality management in the past years with the major objective of improving the capacity of TC Members on integrated data quality control and processing.Despite the significant improvements,the uncertainties and difficulties in processing the full-elements of hydro-meteorological data still persist in hydro-meteorological data.To tackle these challenges and further enhance the data quality management system,the integration of AI technology shows great promise.By examining the data quality management system at World Meteorological Organization(WMO)as a starting point,this paper explored how related organizations in China,Japan,Malaysia,Philippines and Republic of Korea,manage the quality of hydro-meteorological data;reviewed the current status of hydro-meteorological data quality control in TC Members,and discussed the potential areas to be enhanced in future.

Real-time flood forecast and flood alert map over the Huaihe River Basin in China using a coupled hydro-meteorological modeling system

A coupled hydro-meteorological modeling system is established for real-time flood forecast and flood alert over the Huaihe River Basin in China. The system consists of the mesoscale atmospheric model MC2 (Canadian Mesoscale Compressible Community) that is one-way coupled to the Chinese Xinanjiang distributed hydrological model, a grid-based flow routing model, and a module for acquiring real-time gauge precipitation. The system had been successfully tested in a hindcast mode using 1998 and 2003 flood cases in the basin, and has been running daily in a real-time mode for the summers of 2005 and 2006 over the Wangjiaba sub-basin of the Huaihe River Basin. The MC2 precipitation combined with gauge values is used to drive the Xinanjiang model for hydrograph prediction and production of flood alert map. The performance of the system is illustrated through an examination of real-time flood forecasts for the severe flood case of July 4―15, 2005 over the sub-basin, which was the first and largest flood event encountered to date. The 96-h forecasts of MC2 precipitation are first evaluated using observations from 41 rain gauges over the sub-basin. The forecast hydrograph is then validated with observations at the Wangjiaba outlet of the sub-basin. MC2 precipitation generally compares well with gauge values. The flood peak was predicted well in both timing and intensity in the 96-hour forecast using the combined gauge-MC2 precipitation. The real-time flood alert map can spatially display the propagation of forecast floods over the sub-basin. Our forecast hydrograph was used as opera-tional guidance by the Bureau of Hydrograph, Ministry of Water Resources. Such guidance has been proven very useful for the Office of State Flood Control and Drought Relief Headquarters in operational decision making for flood management. The encouraging results demonstrate the potential of using mesoscale atmospheric model precipitation for real-time flood forecast, which can result in a longer lead time compared to traditional methods.

Impact-based forecasting for improving the capacity of typhoon-related disaster risk reduction in typhoon committee region

The two most common types of disasters caused by natural hazards in the Asia-Pacific region are floods and storms,many of them associated with typhoon(tropical cyclone)related impacts.To improve the capacity of typhoon-related disaster risk reduction so as to maximum reduce the losses of people’s life and properties,the decision makers and the public are imminently demanding the information of the targeted impact caused by typhoon.As the front line in hydro-meteorological disaster prevention and mitigation against the typhoon-related disasters,National Meteorological and Hydrological Services(NMHSs)in TC Members have recognized that forecasting impact became more important than forecasting pure causing-disaster elements.Impact-based forecasting signals an evolution from“what the weather will be”to“what the weather will do”.Many things change as impact based forecasts evolve from previous weather forecasts.To enhance impact-based typhoon forecasting,the Typhoon Committee added it into the new updated Strategic Plan 2022–2026.This paper briefed generally the concept of impact based forecasting,introduced the implementation and progresses on typhoon impact based forecasting in TC Members in recent years,and initially discussed the measures and direction for enhancement of impact-based typhoon forecasting and early warning services in future.