Оценка эрозионного потенциала осадков для азиатской части России
Исследование выполнено при финансовой поддержке государственного задания КФУ (проект № FZSM-2026-0017).
DOI:
https://doi.org/10.52575/2712-7443-2026-50-3-538-554Ключевые слова:
метеостанции, плювиограммы, эрозионная активность дождей, временная динамика, USLE/RUSLE, GAM-модель, эрозия почв, ливневой смывАннотация
Эрозионный потенциал осадков (R-фактор) является одним из ключевых параметров в эрозионных моделях USLE/RUSLE, определяя интенсивность дождевого (ливневого) смыва почв. Его количественная оценка затруднена по причине отсутствия массового количественного материала по интенсивности осадков на метеостанциях, особенно это характерно для территории азиатской части России на фоне происходящих климатических изменений. Исследования направлены на разработку методики расчета R-фактора для азиатского макрорегиона России на основе данных срочных наблюдений за осадками. В основе методологии лежит комбинация расчетов эрозионной активности дождевых событий (Rs) по данным автоматических метеостанций с 10-минутным разрешением и применения обобщенно-аддитивных моделей (GAM) для прогнозирования Rs на метеостанциях Росгидромета. Разработанная GAM-модель объясняет 94,6 % изменчивости логарифма Rs и позволяет восстановить временные ряды R-фактора с 1966 по 2021 гг. для 328 метеостанций этого макрорегиона страны. Установлено, что среднемноголетние значения R-фактора за период 1966–1985 гг. хорошо согласуются с ранее полученными референсными данными Г.А. Ларионова. Анализ временной динамики на 85 % метеостанций не выявил статистически значимых трендов R-фактора за выбранный 56-летний период по всему макрорегиону, а наблюдаемые изменения не превышают 1 % от средних значений. Разработанная методика позволяет получать современные помесячные и годовые оценки R-фактора на метеостанциях для всех лет наблюдений, а также выполнять среднемноголетние обобщения за заданный период.
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Список источников
Архив всероссийского научно-исследовательского института гидрометеорологической информации – Мирового центра данных. Электронный ресурс. URL: http://meteo.ru/data/ (дата обращения 08.05.2026).
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