ВОЗМОЖНОСТИ КРАТКОСРОЧНОГО ПРОГНОЗИРОВАНИЯ СТОКА МАЛОЙ РЕКИ С ИСПОЛЬЗОВАНИЕМ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ

The paper addresses prospects for short-term (from 1 to 7 days) forecasting of river streamflow runoff based on several machine learning methods: multiple linear regression (LM) model, a multilayer perceptron (MLP) artificial neural network, and a recurrent artificial neural network with long short-term memory (LSTM). Methods for expanding the set of predictors for model construction are proposed, and the possibility of random shuffling of the time-series of predictors for model calibration and verification are assessed. The object of the study is the small river of Central Russia – river Protva (Spas-Zagorie gauge). Current and lagged values of streamflow discharge at the gauge and daily precipitation at local weather stations are used as predictors for the model, as well as moisture index and evaporation rate. The obtained results show the possibility of constructing an effective operational forecasting system for short-term runoff forecasting. The study revealed the applicability of artificial neural network models, acceptable for operational practice, using all available hydrometeorological information on the catchment, as they showed the most stable results at all lead times from 1 to 7 days. In contrast to the linear model, which efficiency decreases after lead time of more than 3 days, the artificial neural networks models have higher forecast efficiency up to 7 days. The results obtained are robust for all phases of the water regime, both spring floods and summer floods. The software implementation of the models is made on the basis of open software libraries in the Python language, which makes it possible to widely use the methods for scientific research and applied problems.В статье исследуются возможности краткосрочного (от 1 до 7 суток) прогнозирования расходов воды на основе нескольких методов машинного обучения: модели множественной линейной регрессии, искусственной нейронной сети по типу многослойного перцептрона и рекуррентной искусственной нейронной сети с долгосрочной кратковременной памятью. Предлагаются методы расширения набора предикторов для построения моделей и исследуется возможность случайного перемешивания хронологического ряда предикторов для калибровки и верификации моделей как повышающая устойчивость результатов прогноза. В качестве объекта исследования используется малая река Средней полосы России – река Протва (гидрометрический пост Спас-Загорье). В качестве предикторов используются расходы воды на посту и суточные суммы осадков на трех ближайших метеостанциях в текущий момент времени (сутки) и со сдвигом назад до 7 суток, а также индекс увлажнения бассейна и характеристики температуры воздуха и испарения. На конкретном примере показана возможность построения эффективной оперативной прогностической системы для краткосрочного прогнозирования стока. Исследование выявило приемлемую для оперативной практики применимость моделей искусственных нейронных сетей, использующих всю доступную гидрометеорологическую информацию на водосборе, как показавших наиболее устойчивые результаты на всех заблаговременностях от 1 до 7 суток. Так, в отличие от линейной прогностической модели, эффективность которой снижается на заблаговременностях более 3 суток, модели искусственных нейронных сетей показали высокую эффективность прогноза до 7 суток. Полученные результаты устойчивы для всех фаз водного режима, как весеннего половодья, так и летних паводков. Программная реализация моделей выполнена на основании открытых программных библиотек на языке Python, что показывает возможность широкого использования описанных методик для научных исследований и прикладных задач

ВОЗМОЖНОСТИ ОЦЕНИВАНИЯ БАССЕЙНОВОЙ ТРАНСПИРАЦИИ НА ОСНОВЕ ИЗМЕРЕНИЯ СТВОЛОВОГО СОКОДВИЖЕНИЯ: ПОСТАНОВКА ЗАДАЧИ

Study of seasonal dynamics and evapotranspiration volume of forested catchments (mainly forest stand transpiration) is the relevant objective for fundamental knowledge and practical applications. However, there are many difficulties: labor efforts of direct observations, many factors affecting against each other, observational data scaling and so on. As a result, evapotranspiration during hydrological modeling is determined by the leftover principle and simplified techniques, leading to wrong representation of water balance structure. The presented article deals with the first results of our research group focused on setting up field measurements of xylem sap flow using trunk sap flow measuring sensors as well as development of sap flow assessment methods for individual trees and whole catchment. The investigations were performed for mixed coniferous-broad leaved forests at the territory of the Central Sikhote-Alin’ within Verkhneussuriyskiy biogeocenotical station of FSC of the East Asia Terrestrial Biodiversity FEB RAS. This site is used for water balance measuring surveys from 2011. Sap flow was measured continuously during June-October of 2019 on one of the local dominant tree species. Apparently, such investigations are novel for the Russian Far East region. It is expected that direct sap flow measurements for individual trees refinement methods, data scaling and its integration to the hydrometeorological observations will help to make a comprehensive analysis of catchments water balance and to integrate measured data into hydrological models.Изучение сезонной динамики и объемов суммарного испарения лесных водосборов (главным образом транспирации древостоев) является актуальнейшей задачей как в фундаментальном, так и прикладном аспектах. Ее решение связано с рядом сложностей: трудоемкость прямого наблюдения, наличие большого количества влияющих друг на друга факторов, необходимость распространения данных точечных измерений на площадь и многие другие. Это приводит к тому, что при моделировании водного баланса речных бассейнов испарение определяется по упрощенным схемам, остаточному принципу, что ведет к неправильному отражению структуры водного баланса. Настоящая статья представляет первые результаты усилий инициативного коллектива исследователей, направленных на постановку экспериментальных измерений ксилемного потока с использованием современных датчиков стволового сокодвижения, а также развития методов оценки транспирации как отдельных деревьев, так и бассейновой транспирации на основе этих данных. Исследование проведено на территории смешанных хвойно-широколиственных лесов Центрального Сихотэ-Алиня в пределах экспериментального водосбора, входящего в состав Верхнеуссурийского биогеоценотического стационара ФНЦ Биоразнообразия ДВО РАН, на котором рабочей группой возобновлены воднобалансовые работы в 2011 г. и в настоящее время являются уже постоянными. Регистрация стволового сокодвижения выполнялась в период с июня по начало октября 2019 года на одном из доминантных видов местного растительного сообщества. В Дальневосточном регионе России работы такого плана, по-видимому, проведены впервые. Предполагается, что отработка методов оценки прямых измерений транспирации на уровне отдельных деревьев, попытка пространственной генерализации на территорию топологического масштаба и вовлечение полученной информации в комплекс гидрометеорологических наблюдений позволят выполнить исчерпывающий анализ водного баланса в пределах малого речного бассейна и интегрировать поток измеряемых данных по испарению в гидрологические модели. &nbsp

Twenty-three unsolved problems in hydrology (UPH) – a community perspective

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focussed on process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come

Influence of Topographic Characteristics on the Adaptive Time Interval for Diffusion Wave Simulation

Frequent flash floods in recent years have resulted in a major impact on the living environment, urban planning, economic system and flood control facilities of residents around the world; therefore, the establishment of disaster management and flood warning systems is an urgent task, required for government units to propose flood mitigation measures. To conserve the numerical accuracy and maintain stability for explicit scheme, the Courant⁻Friedrich⁻Lewy (CFL) condition is necessarily enforced, and it is conducted to regulate the relation between the numerical marching speed and wave celerity. On the other hand, to avoid the problem of flow reflux between adjacent grids in executing 2D floodplain simulation, another restriction on time intervals, known as the Hunter condition, was devised in an earlier study. The objective of this study was to analyze the spatial and temporal distribution of these two time-interval restrictions during runoff simulations. Via a case study of the Komarovsky River Basin in Russia, the results show that at the beginning of a storm, the computational time interval is restricted by the CFL condition along the upstream steep hillsides, and the time interval is subject to the Hunter condition in the mainstream during the occurrence of the main storm. The reason of a reduction in computational efficiency, which is a common problem in conducting distributed routing, was clearly explained. To relax the time-interval restrictions for efficient flood forecasting, the research findings also indicate the importance of integrating modified hydrological models proposed in recent studies

How well can machine learning models perform without hydrologists?: Application of rational feature selection to improve hydrological forecasting

With more machine learning methods being involved in social and environmental research activities, we are addressing the role of available information for model training in model performance. We tested the abilities of several machine learning models for short-term hydrological forecasting by inferring linkages with all available predictors or only with those pre-selected by a hydrologist. The models used in this study were multivariate linear regression, the M5 model tree, multilayer perceptron (MLP) artificial neural network, and the long short-term memory (LSTM) model. We used two river catchments in contrasting runoff generation conditions to try to infer the ability of different model structures to automatically select the best predictor set from all those available in the dataset and compared models’ performance with that of a model operating on predictors prescribed by a hydrologist. Additionally, we tested how shuffling of the initial dataset improved model performance. We can conclude that in rainfall-driven catchments, the models performed generally better on a dataset prescribed by a hydrologist, while in mixed-snowmelt and baseflow-driven catchments, the automatic selection of predictors was preferable.Water Resource

Comparing the Runoff Decompositions of Small Experimental Catchments: End-Member Mixing Analysis (EMMA) vs. Hydrological Modelling

This study is focused on the comparison of streamflow composition simulated with three well-known rainfall–runoff (RR) models (ECOMAG, HBV, SWAT) against hydrograph decomposition evaluated with End-Member Mixing Analysis (EMMA). In situ observations at two small mountain testbed catchments located in the south of Pacific Russia are used. All applied RR models and EMMA analysis demonstrate that two neighboring catchments disagree significantly on the mutual dynamics of the runoff sources. The RR models' benchmark test is based on proximity to EMMA hydrograph composition. Different aggregation intervals (season, month, and pentad) were applied to find a reasonable generalization period ensuring the clarity of results. ECOMAG is most conformable to EMMA outcome; HBV reflects flood events well enough; SWAT exhibits distinctive behavior compared to the other models. It is shown that, along with standard efficiency criteria of simulated and observed runoff proximity, EMMA analysis might provide useful auxiliary information for the validation of modelling results

The Effect of Atmospheric Pressure Variations on the Suprapermafrost Groundwater Level and Runoff of Small Rivers in the Anadyr Lowlands, Northeast Russia

The present-day models of the hydrological regime of soils and river basins do not include a hypothesis regarding the effect of atmospheric pressure on hydrological processes (baric effect), which is assumed negligible. However, their manifestations are likely, considering the mechanical and hydrophysical properties of shallow peat-bog soils (plasticity and elasticity, high moisture-retention capacity, the ability to swell and shrink) and the important role of undecomposed plant remains. The effect of atmospheric pressure variations on level changes in a suprapermafrost aquifer was detected using field and laboratory experiments in shallow peat and peaty tundra soils in the Anadyr Lowlands, Northeast Russia. One can see this effect in the runoff regime of 1st–4th orders streams. The manifestations of this phenomenon can differ, and in particular, they can be directed oppositely. The changes in the level and storage of suprapermafrost gravitational water could be caused only by synchronous (in phase opposition) changes in capillary water fringe above the groundwater table. To explain the observed phenomena, a conceptual model is developed based on the analysis of the balance of forces and water balance in a system of elastic capillaries. Not being complete and perfect, the model reproduces qualitatively the main observed cases of the response to air pressure changes, proving the effect itself, and suggests the likely localization of its mechanisms. A shallow suprapermafrost groundwater table in contact with the peat bottom, as well as incomplete (below the full moisture capacity) water saturation of peat soil horizons, appear to be circumstances of the baric effect on tundra shallow subsurface aquifers. Favorable conditions for the baric effect in a soil profile include a high elasticity of peat-soil matrix, high and variable values of porosity and water yield of peat and moss cover, and, at the catchment scale, a high proportion of coverage by these types of soils. A full-scale study of a mechanism of baric effect on a suprapermafrost tundra aquifer requires numerous laboratory and field experiments, that must be much better equipped than presented in our study. It is also welcomed alternative hypotheses regarding the aquifer water level response to changes in air pressure if the observed macroscopic effects at any alternative occurrence could be quite similar

The Effect of Atmospheric Pressure Variations on the Suprapermafrost Groundwater Level and Runoff of Small Rivers in the Anadyr Lowlands, Northeast Russia

The present-day models of the hydrological regime of soils and river basins do not include a hypothesis regarding the effect of atmospheric pressure on hydrological processes (baric effect), which is assumed negligible. However, their manifestations are likely, considering the mechanical and hydrophysical properties of shallow peat-bog soils (plasticity and elasticity, high moisture-retention capacity, the ability to swell and shrink) and the important role of undecomposed plant remains. The effect of atmospheric pressure variations on level changes in a suprapermafrost aquifer was detected using field and laboratory experiments in shallow peat and peaty tundra soils in the Anadyr Lowlands, Northeast Russia. One can see this effect in the runoff regime of 1st–4th orders streams. The manifestations of this phenomenon can differ, and in particular, they can be directed oppositely. The changes in the level and storage of suprapermafrost gravitational water could be caused only by synchronous (in phase opposition) changes in capillary water fringe above the groundwater table. To explain the observed phenomena, a conceptual model is developed based on the analysis of the balance of forces and water balance in a system of elastic capillaries. Not being complete and perfect, the model reproduces qualitatively the main observed cases of the response to air pressure changes, proving the effect itself, and suggests the likely localization of its mechanisms. A shallow suprapermafrost groundwater table in contact with the peat bottom, as well as incomplete (below the full moisture capacity) water saturation of peat soil horizons, appear to be circumstances of the baric effect on tundra shallow subsurface aquifers. Favorable conditions for the baric effect in a soil profile include a high elasticity of peat-soil matrix, high and variable values of porosity and water yield of peat and moss cover, and, at the catchment scale, a high proportion of coverage by these types of soils. A full-scale study of a mechanism of baric effect on a suprapermafrost tundra aquifer requires numerous laboratory and field experiments, that must be much better equipped than presented in our study. It is also welcomed alternative hypotheses regarding the aquifer water level response to changes in air pressure if the observed macroscopic effects at any alternative occurrence could be quite similar

Landscape-permafrost conditions and factors of summer runoff formation of small coastal lowland rivers

River feed and flow regime in the Anadyr lowland remain stable with significant interannual fluctuations in the amount of summer precipitation (70-180 mm). The lack of summer precipitation is compensated by the suprapermafrost groundwater of the active layer, which is formed by meltwater from seasonal underground ice. In July 2019, complex permafrost-hydrological studies were conducted in the Ugolnaya-Dionisia river basin (Chukotka, Russia) to determine the patterns of formation and dynamics of underground and surface runoff. Seasonal active layer groundwater storage that formed as a result of the melting of seasonal ice was estimated. The territory was classified according to the unite discharge, potential and established water sources. Patterns and factors of seasonal and daily dynamics of the river regime are revealed