Land | Special Issue : Advances in Hydrologic and Water Quality Modeling of Water Systems

Research

19 pages, 3533 KiB

Open AccessArticle

Method for Environmental Flows Regulation and Early Warning with Remote Sensing and Land Cover Data

by Yuming Lu, Bingfang Wu, Nana Yan, Weiwei Zhu, Hongwei Zeng and Linjiang Wang

Land 2021, 10(11), 1216; https://doi.org/10.3390/land10111216 - 10 Nov 2021

Viewed by 1667

Environmental flows play a vital role in ecosystem and water resource management. The regulation and management of environmental flows can improve the function and stability of river and lake ecosystems. However, current methods for assessing environmental flows mainly emphasize water management, and there [...] Read more.

Environmental flows play a vital role in ecosystem and water resource management. The regulation and management of environmental flows can improve the function and stability of river and lake ecosystems. However, current methods for assessing environmental flows mainly emphasize water management, and there is no complete set of regulations or early warning systems, especially in arid and semiarid basins. In this study, we proposed a method for environmental flows regulation and early warning with remote sensing and land cover data and carried out a case study in the Yongding River Basin, which is a basin typical of arid and semiarid areas. The results show that from 2001 to 2014 the mean precipitation was 17.90 × 10⁹ m³, and the mean water consumption was 19.42 × 10⁹ m³, indicating that the basin water budget was clearly unbalanced and that there was an overall deficiency. Notably, from 2005 to 2014 and in 2014, the available consumable water was less than the water consumption required for human activities, which both showed a trend of further reduction; therefore, long-term and annual early warnings should have been issued. The methods applied in this study and the study outcomes could help in the development of comprehensive management and ecological restoration plans, further improving the ecological environments of river basins. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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31 pages, 5342 KiB

Open AccessFeature PaperArticle

Modelling the Event-Based Hydrological Response of Mediterranean Forests to Prescribed Fire and Soil Mulching with Fern Using the Curve Number, Horton and USLE-Family (Universal Soil Loss Equation) Models

by Bruno Gianmarco Carra, Giuseppe Bombino, Manuel Esteban Lucas-Borja, Pietro Denisi, Pedro Antonio Plaza-Álvarez and Demetrio Antonio Zema

Land 2021, 10(11), 1166; https://doi.org/10.3390/land10111166 - 31 Oct 2021

Cited by 3 | Viewed by 2083

Abstract

The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this [...] Read more.

The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this gap, this study evaluates the prediction capability for runoff and soil loss of the SCS-CN, Horton, MUSLE, and USLE-M models in three forests (pine, chestnut, and oak) in Southern Italy. The investigation was carried out at plot and event scales throughout one year, after a prescribed fire and post-fire soil mulching with fern. The SCS-CN and USLE-M models were accurate in predicting runoff volume and soil loss, respectively. In contrast, poor predictions of the modelled hydrological variables were provided by the models in unburned plots, and by the Horton and MUSLE models for all soil conditions. This inaccuracy may have been due to the fact that the runoff and erosion generation mechanisms were saturation-excess and rainsplash, while the Horton and MUSLE models better simulate infiltration-excess and overland flow processes, respectively. For the SCS-CN and USLE-M models, calibration was needed to obtain accurate predictions of surface runoff and soil loss; furthermore, different CNs and C factors must be input throughout the year to simulate the variability of the hydrological response of soil after fire. After calibration, two sets of CNs and C-factor values were suggested for applications of the SCS-CN and USLE-M models, after prescribed fire and fern mulching in Mediterranean forests. Once validated in a wider range of environmental contexts, these models may support land managers in controlling the hydrology of Mediterranean forests that are prone to wildfire risks. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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22 pages, 2583 KiB

Open AccessArticle

Watershed Response to Legacy Phosphorus and Best Management Practices in an Impacted Agricultural Watershed in Florida, U.S.A.

by Yogesh P. Khare, Rajendra Paudel, Ruscena Wiederholt, Anteneh Z. Abiy, Thomas Van Lent, Stephen E. Davis and Younggu Her

Land 2021, 10(9), 977; https://doi.org/10.3390/land10090977 - 16 Sep 2021

Cited by 13 | Viewed by 3614

Abstract

Soil phosphorus (P) built up due to past management practices, legacy P, in the Lake Okeechobee Watershed (LOW) in south-central Florida, U.S.A., is often discussed as the root cause of lake eutrophication. Improvement of the lake’s water quality requires the identification of critical [...] Read more.

Soil phosphorus (P) built up due to past management practices, legacy P, in the Lake Okeechobee Watershed (LOW) in south-central Florida, U.S.A., is often discussed as the root cause of lake eutrophication. Improvement of the lake’s water quality requires the identification of critical P sources and quantifying their contributions. We performed a global sensitivity analysis of the Watershed Assessment Model (WAM), a common evaluation tool in LOW environmental planning, using the Morris method. A pre-calibrated WAM setup (Baseline) of the LOW sub-watershed, Taylor Creek Nubbin Slough (TCNS), was used as a test case. Eight scenarios were formulated to estimate the contributions of various P sources. The Morris analysis indicated that total phosphorus (TP) loads were highly sensitive to legacy P in improved pastures, the major land use covering 46.2% of TCNS. The scenario modeling revealed that legacy P, inorganic fertilizers, and other sources contribute 63%, 10%, and 32%, respectively, to the Baseline TP load of 111.3 metric tons/y to the lake. Improved pastures, dairies, citrus, and field crops are the top TP load contributors. Our results have important implications for water quality improvement plans in the LOW and highlighted the need for accurate spatial mapping of legacy P and incorporation of such information in modeling efforts for watersheds demonstrating legacy P problems. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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24 pages, 2745 KiB

Open AccessFeature PaperArticle

Forecasts of Opportunity for Northern California Soil Moisture

by Cécile Penland, Megan D. Fowler, Darren L. Jackson and Robert Cifelli

Land 2021, 10(7), 713; https://doi.org/10.3390/land10070713 - 6 Jul 2021

Cited by 1 | Viewed by 2328

Abstract

Soil moisture anomalies underpin a number of critical hydrological phenomena with socioeconomic consequences, yet systematic studies of soil moisture predictability are limited. Here, we use a data-adaptive technique, Linear Inverse Modeling, which has proved useful as an indication of predictability in other fields, [...] Read more.

Soil moisture anomalies underpin a number of critical hydrological phenomena with socioeconomic consequences, yet systematic studies of soil moisture predictability are limited. Here, we use a data-adaptive technique, Linear Inverse Modeling, which has proved useful as an indication of predictability in other fields, to investigate the predictability of soil moisture in northern California. This approach yields a model of soil moisture at 10 stations in the region, with results that indicate the possibility of skillful forecasts at each for lead times of 1–2 weeks. An important advantage of this model is the a priori identification of forecasts of opportunity—conditions under which the model’s forecasts may be expected to have particularly high skill. Given that forecast errors (and inversely, their skill) can be estimated in advance, these findings have the potential to greatly increase the utility of soil moisture forecasts for practical applications including drought and flood forecasting. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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29 pages, 4724 KiB

Open AccessArticle

Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia

by Nekruz Gulahmadov, Yaning Chen, Aminjon Gulakhmadov, Moldir Rakhimova and Manuchekhr Gulakhmadov

Land 2021, 10(5), 525; https://doi.org/10.3390/land10050525 - 14 May 2021

Cited by 9 | Viewed by 3264

Abstract

Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are [...] Read more.

Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are known to have caused changes to the hydrological cycle. Therefore, quantifying the net influence of anthropogenic contribution to the runoff changes is a challenge. This study applied the original and modified Mann–Kendall trend test, including the Sen’s slope test, Pettitt’s test, double cumulative curve, and elasticity methods. These methods were applied to determine the historical trends, magnitude changes and change points of the temperature, precipitation, potential evapotranspiration, and runoff from 1950 to 2016. In addition, the contributions of climate change and anthropogenic activities to runoff changes in the KRB were evaluated. The trend analysis showed a significant increasing trend in annual temperature and potential evapotranspiration, while the annual precipitation trend showed an insignificant decreasing trend during the 1950–2016 time period. The change point in runoff occurred in 1986 in the upstream region and 1991 in the downstream region. Further, the time series (1950–2016) is separated into the prior impacted period (1950–1986 and 1950–1991) and post impacted period (1987–2016 and 1992–2016) for the upstream and downstream regions, respectively. During the post impacted period, climate change and anthropogenic activities contributed to 87.96% and 12.04% in the upstream region and 7.53% and 92.47% in the downstream region of the KRB. The results showed that in runoff changes, the anthropogenic activities played a dominant role in the downstream (97.78%) and the climate change impacts played a dominant factor in the upstream region (87.96%). In the land-use type changes, the dominant role was played by construction land, which showed that the area from 248.63 km² in 1990 increased to 685.45 km² (175.69%) in 2015. These findings suggest that it is essential to adopt effective steps for the sustainable development of the ecological, hydrological, and social order in the KRB in Central Asia. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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19 pages, 3596 KiB

Open AccessArticle

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

by Guangxing Ji, Zhizhu Lai, Haibin Xia, Hao Liu and Zheng Wang

Land 2021, 10(4), 421; https://doi.org/10.3390/land10040421 - 15 Apr 2021

Cited by 43 | Viewed by 4092

Abstract

The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the [...] Read more.

The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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16 pages, 4296 KiB

Open AccessArticle

Optical Spectral Tools for Diagnosing Water Media Quality: A Case Study on the Angara/Yenisey River System in the Siberian Region

by Costas A. Varotsos, Vladimir F. Krapivin, Ferdenant A. Mkrtchyan and Yong Xue

Land 2021, 10(4), 342; https://doi.org/10.3390/land10040342 - 27 Mar 2021

Cited by 11 | Viewed by 4332

Abstract

This paper presents the results of spectral optical measurements of hydrochemical characteristics in the Angara/Yenisei river system (AYRS) extending from Lake Baikal to the estuary of the Yenisei River. For the first time, such large-scale observations were made as part of a joint [...] Read more.

This paper presents the results of spectral optical measurements of hydrochemical characteristics in the Angara/Yenisei river system (AYRS) extending from Lake Baikal to the estuary of the Yenisei River. For the first time, such large-scale observations were made as part of a joint American-Russian expedition in July and August of 1995, when concentrations of radionuclides, heavy metals, and oil hydrocarbons were assessed. The results of this study were obtained as part of the Russian hydrochemical expedition in July and August, 2019. For in situ measurements and sampling at 14 sampling sites, three optical spectral instruments and appropriate software were used, including big data processing algorithms and an AYRS simulation model. The results show that the water quality in AYRS has improved slightly due to the reasonably reduced anthropogenic industrial impact. Chemical concentrations in water have been found to vary along the Angara River depending on the location of the dams. The results of in situ measurements and modeling evaluations are given. To overcome the uncertainties in the data caused by the large monitoring area, it is recommended to use the combined AYRS simulation model and the universal 8-channel spectrophotometer installed on a fixed platform for continuous monitoring. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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14 pages, 3803 KiB

Open AccessArticle

Development of Flood Damage Regression Models by Rainfall Identification Reflecting Landscape Features in Gangwon Province, the Republic of Korea

by Hyun Il Choi

Land 2021, 10(2), 123; https://doi.org/10.3390/land10020123 - 27 Jan 2021

Cited by 4 | Viewed by 2811

Abstract

Torrential rainfall events associated with rainstorms and typhoons are the main causes of flood-related economic losses in Gangwon Province, Republic of Korea. The frequency and severity of flood damage have been increasing due to frequent extreme rainfall events as a result of climate [...] Read more.

Torrential rainfall events associated with rainstorms and typhoons are the main causes of flood-related economic losses in Gangwon Province, Republic of Korea. The frequency and severity of flood damage have been increasing due to frequent extreme rainfall events as a result of climate change. Rainfall is a major cause of flood damage for the study site, given a strong relationship between the probability of flood damage over the last two decades and the maximum rainfall for 6 and 24 h durations in the 18 administrative districts of Gangwon Province. This study aims to develop flood damage regression models by rainfall identification for use in a simplified and efficient assessment of flood damage risk in ungauged or poorly gauged regions. Optimal simple regression models were selected from four types of non-linear functions with one of five composite predictors averaged for the two rainfall datasets. To identify appropriate predictor rainfall variables indicative of regional landscape features, the relationships between the composite rainfall predictor and landscape characteristics such as district size, topographic features, and urbanization rate were interpreted. The proposed optimal regression models may provide governments and policymakers with an efficient flood damage risk map simply using a regression outcome to design or forecast rainfall data. Full article

(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)

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