Preface to the 2024.Q1 Edition
This book serves as a study guide and a detailed examination of semi-arid Central Asia’s hydrology, specifically focusing on hydrological modeling applications within the region. Designed for students and emerging professionals in Central Asia, it aims to impart contemporary hydrological modeling techniques through practical examples. The book’s core centers on case studies from the Syr Darya and Amu Darya river basins, providing a hands-on approach to learning that can be adapted to other contexts.
Hydrological models vary widely, encompassing different types and approaches. Among these, hydrological water balance models—also referred to as rainfall-runoff models in this text—are designed to enhance our understanding of how available water is distributed into various flows and storage areas over time within a given natural system. This system typically comprises interconnected segments, including surface water and both unsaturated (soil moisture) and saturated (groundwater) zones, through which these models simulate water movement. Their primary application lies in water management and planning, particularly for devising basin strategies amidst changing climates and growing populations, aiming to distribute water among diverse needs and users. Additionally, they serve operational purposes, helping bridge the gap between supply and demand in real-time management and facilitating short-term forecasts.
In scenarios where extensive data is available, empirical models become viable. Unlike their counterparts, these models do not simulate the water balance of each compartment explicitly. Instead, they identify patterns in historical data, such as discharge, temperature, precipitation, and snow cover. They leverage these relationships to forecast key variables like discharge and water levels at a particular location. These models are typically used in short-term forecasting and operational management.
Part I of the book lays out the fundamental hydro-climatological features of the region, drawing inspiration from Victor Shults’ seminal work, “Rivers of Middle Asia” (Shults 1965). By aggregating extensive in-situ hydrological data from across the region and integrating it with a wealth of newly accessible data, we achieve a comprehensive and modern overview of Central Asian hydrology, continuing in Shults’ tradition.
This section focuses on two key basins for detailed case studies: the Gunt River Basin within the Amu Darya catchment and the Chirchik River Basin in the Syr Darya catchment. The examination of these basins utilizes data from the Central Asian National Meteorological and Hydrological Services, along with global, publicly available hydro-climatological and land cover datasets, as well as cryosphere data. These initial chapters aim to acquaint students with the preliminary steps essential for hydrological modeling. This involves a solid understanding of the system under study through an extensive hydro-climatological assessment of the area.
Part II constitutes a substantial portion of the book and discusses various open data sources relevant to hydrological modeling. It covers the process of data retrieval and preparation, encompassing information on topography, land use, climate reanalysis, biophysical climate parameters, climate projections, and snow and ice data. Given the extensive effort needed to prepare these datasets for modeling, this section emphasizes practical workflows. These are designed to streamline the preparation, control, and management of such data, making them more accessible in hydrological models.
Part III of the book introduces and explores five distinct modeling approaches. Firstly, it presents detailed hydrological-hydraulic modeling for individual river basins, typically used for analyzing trade-offs among various water uses and users within a basin, both in planning and under different climate scenarios. These models can also operate in real-time to address immediate management challenges. Secondly, it delves into long-term water balance modeling using the Budyko framework, applying it to a comprehensive dataset from the region to offer insights into regional hydrological changes attributable to climate variations, particularly where detailed modeling of numerous rivers is not feasible. Thirdly, this part introduces empirical data-driven models for forecasting discharge at specific basin locations, dependent on the availability of extensive measured discharge data. Additionally, a dedicated chapter focuses on glacier melt discharge, highlighting its significance on a climatic scale and seasonally, especially during months like July and August when glacier melt significantly contributes to river discharge in glaciated catchments. Lastly, the book addresses the application of hydrological models in climate change research, offering guidance on setting up and executing climate change scenarios for impact quantification.
The book/study guide is accompanied by a Study Exercise Pack that encompasses data from 7 Central Asian catchments, which can be used by students to learn and apply skills acquired to real-world examples in the region. The Exercise Pack can accessed and downloaded here. Furthermore, a dedicated R Package has been developed, which implements many of the data analyses and processing steps shown in this book (see also Section for more information).
With everything that is presented, the focus is on the use of open-source and free software. For data preparation and analysis, as well as for water balance and empirical modeling, R and RStudio are utilized (R Core Team 2022). For the processing of geographic data, workflows in QGIS are demonstrated (QGIS Development Team 2021). For hydrological-hydraulic modeling, the free RS MINERVE is utilized. It is an environment for the modeling of free surface runoff flow formation and propagation (Foehn et al. 2020; Garcia Hernandez et al. 2020). The reader is expected to have a basic understanding of R and QGIS and how to use this software for data analysis and processing.
The outlook of learning hydrology together with quantitative geospatial analysis and programming may sound overwhelming at the beginning. Really, the best way is to dive into the book and learn through the many examples provided. All code with which the analysis and modeling is carried out is provided and can thus be adapted to any other local context or relevant task. So, this handbook on applied hydrological modeling hopefully invites students to learn through experimentation and not to get scared.
Before we get going, here is a small note on how to translate this text into any other language of interest. Should the reader struggle with English, there is a straightforward way to translate this book into any local language spoken in Central Asia, including Russian. The picture below shows a screenshot from the online book translated into Russian language via Google Chrome’s translation service. The screenshot shows how to activate the translation panel (1). The translated book text then appears (2). Alternatively, right-click anywhere on the page. Then, click Translate to [Language].
