Pub Date : 2023-09-29DOI: 10.3389/frwa.2023.1258367
Hoang Tran, Chen Yang, Laura E. Condon, Reed M. Maxwell
Increases in evapotranspiration (ET) from global warming are decreasing streamflow in headwater basins worldwide. However, these streamflow losses do not occur uniformly due to complex topography. To better understand the heterogeneity of streamflow loss, we use the Budyko shape parameter (ω) as a diagnostic tool. We fit ω to 37-year of hydrologic simulation output in the Upper Colorado River Basin (UCRB), an important headwater basin in the US. We split the UCRB into two categories: peak watersheds with high elevation and steep slopes, and valley watersheds with lower elevation and gradual slopes. Our results demonstrate a relationship between streamflow loss and ω. The valley watersheds with greater streamflow loss have ω higher than 3.1, while the peak watersheds with less streamflow loss have an average ω of 1.3. This work highlights the use of ω as an indicator of streamflow loss and could be generalized to other headwater basin systems.
{"title":"The Budyko shape parameter as a descriptive index for streamflow loss","authors":"Hoang Tran, Chen Yang, Laura E. Condon, Reed M. Maxwell","doi":"10.3389/frwa.2023.1258367","DOIUrl":"https://doi.org/10.3389/frwa.2023.1258367","url":null,"abstract":"Increases in evapotranspiration (ET) from global warming are decreasing streamflow in headwater basins worldwide. However, these streamflow losses do not occur uniformly due to complex topography. To better understand the heterogeneity of streamflow loss, we use the Budyko shape parameter (ω) as a diagnostic tool. We fit ω to 37-year of hydrologic simulation output in the Upper Colorado River Basin (UCRB), an important headwater basin in the US. We split the UCRB into two categories: peak watersheds with high elevation and steep slopes, and valley watersheds with lower elevation and gradual slopes. Our results demonstrate a relationship between streamflow loss and ω. The valley watersheds with greater streamflow loss have ω higher than 3.1, while the peak watersheds with less streamflow loss have an average ω of 1.3. This work highlights the use of ω as an indicator of streamflow loss and could be generalized to other headwater basin systems.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135247478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.3389/frwa.2023.1225837
Inna Kurganskaya, Andreas Luttge
The correct quantification of mineral dissolution rates is a critical task for macroscopic reactive transport modeling. Previous studies showed a substantial rate variability of about two orders of magnitude, which cannot be explained by variance of external environmental parameters alone. If the rate cannot be predicted as a constant parameter, then the critical question is whether it can be predicted as a stable reproducible probability distribution. Although a large variety of factors may contribute to the overall variance across the scales, the effect of defect density and defect spatial distribution can be considered as one of the key variance sources. Here, we tested the reproducibility of probability distributions for Kossel crystals with a different amount and spatial configurations of lattice dislocations. We ran several tests on systems with the same configurations and calculated the probabilities of material flux. Surprisingly, we discovered that the density of dislocations has minimal impact on the probability distributions. However, the spatial location of dislocations has a substantial influence on the rate distributions reproducibility. In cases where multiple etch pits operate simultaneously, reproducible rate distributions are found regardless of the number of dislocations. In cases where dislocations formed clusters, one large etch pit controlled the entire surface, and sets of reproducible probability distributions were detected. Then, more complex statistical behavior is expected, since the result is path-dependent. These results have serious consequences for the implementation of rate distributions in reactive transport models. Further studies, however, are needed to provide clear guidance on relating surface morphologies, dislocation distributions, and dissolution rate variance. The role of material-specific properties, such as crystallographic structure and bonding, in rate distributions, should be additionally addressed. The role of grain boundaries, crystal size and crystal habit, including nanoparticulate forms, in rate variance, also should be addressed for practical applications.
{"title":"Probability distributions of mineral dissolution rates: the role of lattice defects","authors":"Inna Kurganskaya, Andreas Luttge","doi":"10.3389/frwa.2023.1225837","DOIUrl":"https://doi.org/10.3389/frwa.2023.1225837","url":null,"abstract":"The correct quantification of mineral dissolution rates is a critical task for macroscopic reactive transport modeling. Previous studies showed a substantial rate variability of about two orders of magnitude, which cannot be explained by variance of external environmental parameters alone. If the rate cannot be predicted as a constant parameter, then the critical question is whether it can be predicted as a stable reproducible probability distribution. Although a large variety of factors may contribute to the overall variance across the scales, the effect of defect density and defect spatial distribution can be considered as one of the key variance sources. Here, we tested the reproducibility of probability distributions for Kossel crystals with a different amount and spatial configurations of lattice dislocations. We ran several tests on systems with the same configurations and calculated the probabilities of material flux. Surprisingly, we discovered that the density of dislocations has minimal impact on the probability distributions. However, the spatial location of dislocations has a substantial influence on the rate distributions reproducibility. In cases where multiple etch pits operate simultaneously, reproducible rate distributions are found regardless of the number of dislocations. In cases where dislocations formed clusters, one large etch pit controlled the entire surface, and sets of reproducible probability distributions were detected. Then, more complex statistical behavior is expected, since the result is path-dependent. These results have serious consequences for the implementation of rate distributions in reactive transport models. Further studies, however, are needed to provide clear guidance on relating surface morphologies, dislocation distributions, and dissolution rate variance. The role of material-specific properties, such as crystallographic structure and bonding, in rate distributions, should be additionally addressed. The role of grain boundaries, crystal size and crystal habit, including nanoparticulate forms, in rate variance, also should be addressed for practical applications.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135425152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.3389/frwa.2023.1283810
E. Kramarsky-Winter, K. Yaniv, Ariel Kushmaro
{"title":"Editorial: Wastewater-based epidemiology as a tool for monitoring public health","authors":"E. Kramarsky-Winter, K. Yaniv, Ariel Kushmaro","doi":"10.3389/frwa.2023.1283810","DOIUrl":"https://doi.org/10.3389/frwa.2023.1283810","url":null,"abstract":"","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"12 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139335453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-25DOI: 10.3389/frwa.2023.1233899
María José Merizalde, Paul Muñoz, Gerald Corzo, David F. Muñoz, Esteban Samaniego, Rolando Célleri
Introduction In complex mountain basins, hydrological forecasting poses a formidable challenge due to the intricacies of runoff generation processes and the limitations of available data. This study explores the enhancement of short-term runoff forecasting models through the utilization of long short-term memory (LSTM) networks. Methods To achieve this, we employed feature engineering (FE) strategies, focusing on geographic data and the Soil Conservation Service Curve Number (SCS-CN) method. Our investigation was conducted in a 3,390 km 2 basin, employing the GSMaP-NRT satellite precipitation product (SPP) to develop forecasting models with lead times of 1, 6, and 11 h. These lead times were selected to address the needs of near-real-time forecasting, flash flood prediction, and basin concentration time assessment, respectively. Results and discussion Our findings demonstrate an improvement in the efficiency of LSTM forecasting models across all lead times, as indicated by Nash-Sutcliffe efficiency values of 0.93 (1 h), 0.77 (6 h), and 0.67 (11 h). Notably, these results are on par with studies relying on ground-based precipitation data. This methodology not only showcases the potential for advanced data-driven runoff models but also underscores the importance of incorporating available geographic information into precipitation-ungauged hydrological systems. The insights derived from this study offer valuable tools for hydrologists and researchers seeking to enhance the accuracy of hydrological forecasting in complex mountain basins.
在复杂的山地流域，由于径流生成过程的复杂性和可用数据的局限性，水文预报提出了一个巨大的挑战。本研究探讨利用长短期记忆(LSTM)网络增强短期径流预测模型。为了实现这一目标，我们采用特征工程(FE)策略，重点关注地理数据和土壤保持服务曲线数(SCS-CN)方法。利用GSMaP-NRT卫星降水产品(SPP)在一个3390 km 2的流域进行了调查，建立了提前期分别为1、6和11 h的预报模型。这些提前期分别用于近实时预报、山洪预报和流域集中时间评估。我们的研究结果表明，LSTM预测模型在所有提前期内的效率都有所提高，Nash-Sutcliffe效率值分别为0.93 (1 h)、0.77 (6 h)和0.67 (11 h)。值得注意的是，这些结果与基于地面降水数据的研究结果相当。这种方法不仅展示了先进的数据驱动径流模型的潜力，而且强调了将现有地理信息纳入未测量降水的水文系统的重要性。从这项研究中获得的见解为寻求提高复杂山区盆地水文预报准确性的水文学家和研究人员提供了有价值的工具。
{"title":"Integrating geographic data and the SCS-CN method with LSTM networks for enhanced runoff forecasting in a complex mountain basin","authors":"María José Merizalde, Paul Muñoz, Gerald Corzo, David F. Muñoz, Esteban Samaniego, Rolando Célleri","doi":"10.3389/frwa.2023.1233899","DOIUrl":"https://doi.org/10.3389/frwa.2023.1233899","url":null,"abstract":"Introduction In complex mountain basins, hydrological forecasting poses a formidable challenge due to the intricacies of runoff generation processes and the limitations of available data. This study explores the enhancement of short-term runoff forecasting models through the utilization of long short-term memory (LSTM) networks. Methods To achieve this, we employed feature engineering (FE) strategies, focusing on geographic data and the Soil Conservation Service Curve Number (SCS-CN) method. Our investigation was conducted in a 3,390 km 2 basin, employing the GSMaP-NRT satellite precipitation product (SPP) to develop forecasting models with lead times of 1, 6, and 11 h. These lead times were selected to address the needs of near-real-time forecasting, flash flood prediction, and basin concentration time assessment, respectively. Results and discussion Our findings demonstrate an improvement in the efficiency of LSTM forecasting models across all lead times, as indicated by Nash-Sutcliffe efficiency values of 0.93 (1 h), 0.77 (6 h), and 0.67 (11 h). Notably, these results are on par with studies relying on ground-based precipitation data. This methodology not only showcases the potential for advanced data-driven runoff models but also underscores the importance of incorporating available geographic information into precipitation-ungauged hydrological systems. The insights derived from this study offer valuable tools for hydrologists and researchers seeking to enhance the accuracy of hydrological forecasting in complex mountain basins.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135864983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.3389/frwa.2023.1278462
Fang Yenn Teo, Faissal Aziz, Silvia Di Francesco, Kristian Förster
{"title":"Editorial: Potential and limitations of Nature-based Solutions (NbS) to global water challenges","authors":"Fang Yenn Teo, Faissal Aziz, Silvia Di Francesco, Kristian Förster","doi":"10.3389/frwa.2023.1278462","DOIUrl":"https://doi.org/10.3389/frwa.2023.1278462","url":null,"abstract":"","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139336975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.3389/frwa.2023.1194540
Haris Uddin Qureshi, Syed Muzzamil Hussain Shah, Fang Yenn Teo
The agriculture sector, due to its significant dependence on climate patterns and water availability, is highly vulnerable to changing climate patterns. Pakistan is an agrarian economy with 30% of its land area under cultivation and 93% of its water resources being utilized for agricultural production. Therefore, the changing climate patterns may adversely affect the agriculture and water resources of the country. This study was conducted to assess the climate variations over the major agro-climatic zones of Sindh and Punjab, which serve as an important hub for the production of major food and cash crops in Pakistan. For this purpose, the climate data of 21 stations were analyzed using the Mann–Kendall test and Sen's slope estimator method for the period 1990–2022. The results obtained from the analysis revealed that, in Sindh, the mean annual temperature rose by ~0.1 to 1.4°C, with ~0.1 to 1.2°C in cotton-wheat Sindh and 0.8 to 1.4°C in rice-other Sindh during the study period. Similarly, in Punjab, the mean annual temperature increased by ~0.1 to 1.0°C, with 0.6 to 0.9°C in cotton-wheat Punjab and 0.2 to 0.6°C in rainfed Punjab. Seasonally, warming was found to be highest during the spring season. The precipitation analysis showed a rising annual precipitation trend in Sindh (+30 to +60 mm) and Punjab (+100 to 300 mm), while the monsoon precipitation increased by ~50 to 200 mm. For winter precipitation, an upward trend was found in mixed Punjab, while the remaining stations showed a declining pattern. Conclusively, the warming temperatures as found in the analysis may result in increased irrigation requirements, soil moisture desiccation, and wilting of crops, ultimately leading to low crop yield and threatening the livelihoods of local farmers. On the other hand, the increasing precipitation may favor national agriculture in terms of less freshwater withdrawals. However, it may also result in increased rainfall-induced floods inundating the crop fields and causing water logging and soil salinization. The study outcomes comprehensively highlighted the prevailing climate trends over the important agro-climatic zones of Pakistan, which may aid in devising an effective climate change adaptation and mitigation strategy to ensure the state of water and food security in the country.
{"title":"Trend assessment of changing climate patterns over the major agro-climatic zones of Sindh and Punjab","authors":"Haris Uddin Qureshi, Syed Muzzamil Hussain Shah, Fang Yenn Teo","doi":"10.3389/frwa.2023.1194540","DOIUrl":"https://doi.org/10.3389/frwa.2023.1194540","url":null,"abstract":"The agriculture sector, due to its significant dependence on climate patterns and water availability, is highly vulnerable to changing climate patterns. Pakistan is an agrarian economy with 30% of its land area under cultivation and 93% of its water resources being utilized for agricultural production. Therefore, the changing climate patterns may adversely affect the agriculture and water resources of the country. This study was conducted to assess the climate variations over the major agro-climatic zones of Sindh and Punjab, which serve as an important hub for the production of major food and cash crops in Pakistan. For this purpose, the climate data of 21 stations were analyzed using the Mann–Kendall test and Sen's slope estimator method for the period 1990–2022. The results obtained from the analysis revealed that, in Sindh, the mean annual temperature rose by ~0.1 to 1.4°C, with ~0.1 to 1.2°C in cotton-wheat Sindh and 0.8 to 1.4°C in rice-other Sindh during the study period. Similarly, in Punjab, the mean annual temperature increased by ~0.1 to 1.0°C, with 0.6 to 0.9°C in cotton-wheat Punjab and 0.2 to 0.6°C in rainfed Punjab. Seasonally, warming was found to be highest during the spring season. The precipitation analysis showed a rising annual precipitation trend in Sindh (+30 to +60 mm) and Punjab (+100 to 300 mm), while the monsoon precipitation increased by ~50 to 200 mm. For winter precipitation, an upward trend was found in mixed Punjab, while the remaining stations showed a declining pattern. Conclusively, the warming temperatures as found in the analysis may result in increased irrigation requirements, soil moisture desiccation, and wilting of crops, ultimately leading to low crop yield and threatening the livelihoods of local farmers. On the other hand, the increasing precipitation may favor national agriculture in terms of less freshwater withdrawals. However, it may also result in increased rainfall-induced floods inundating the crop fields and causing water logging and soil salinization. The study outcomes comprehensively highlighted the prevailing climate trends over the important agro-climatic zones of Pakistan, which may aid in devising an effective climate change adaptation and mitigation strategy to ensure the state of water and food security in the country.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"333 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136016697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.3389/frwa.2023.1258709
S. Bhatti, I. Rana, J. K. Routray
{"title":"Editorial: Flood risk perception, vulnerability, and risk: from assessments to analyses","authors":"S. Bhatti, I. Rana, J. K. Routray","doi":"10.3389/frwa.2023.1258709","DOIUrl":"https://doi.org/10.3389/frwa.2023.1258709","url":null,"abstract":"","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"9 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139338740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.3389/frwa.2023.1244024
Chak-Hau Michael Tso, Eugene Magee, David Huxley, Michael Eastman, Matthew Fry
Nitrogen (N) and phosphorus (P) are essential nutrients necessary for plant growth and support life in aquatic ecosystems. However, excessive N and P can lead to algal blooms that deplete oxygen and lead to fish death and the release of toxins that are harmful to humans. Estimates of N and P levels in rivers are typically calculated at station or grid (>1 km) scale; therefore, it is difficult to visualise the evolution of water quality as water travels downstream. Using a high-resolution reach-scale river network and associating each reach with land cover fractions and catchment descriptors, we trained random forest models on aggregated data (2010–2020) from the Environmental Agency Open Water Quality Data Archive for 2,343 stations to predict long-term nitrate and orthophosphate concentrations at each river reach in Great Britain (GB). We separated the model training and predictions for different seasons to investigate the potential difference in feature importance. Our model predicted concentrations with an average testing coefficient of determination ( R 2 ) of 0.71 for nitrate and 0.58 for orthophosphate using 5-fold cross-validation. Our model showed slightly better performance for higher Strahler stream orders, highlighting the challenges of making predictions in small streams. Our results revealed that arable and horticultural land use is the strongest and most reliable predictor for nitrate, while floodplain extents and standard percentage runoff are stronger predictors for orthophosphate. Nationally, higher orthophosphate concentrations were observed in urbanised areas. This study shows how combining a river network model with machine learning can easily provide a river network understanding of the spatial distribution of water quality levels.
{"title":"River reach-level machine learning estimation of nutrient concentrations in Great Britain","authors":"Chak-Hau Michael Tso, Eugene Magee, David Huxley, Michael Eastman, Matthew Fry","doi":"10.3389/frwa.2023.1244024","DOIUrl":"https://doi.org/10.3389/frwa.2023.1244024","url":null,"abstract":"Nitrogen (N) and phosphorus (P) are essential nutrients necessary for plant growth and support life in aquatic ecosystems. However, excessive N and P can lead to algal blooms that deplete oxygen and lead to fish death and the release of toxins that are harmful to humans. Estimates of N and P levels in rivers are typically calculated at station or grid (>1 km) scale; therefore, it is difficult to visualise the evolution of water quality as water travels downstream. Using a high-resolution reach-scale river network and associating each reach with land cover fractions and catchment descriptors, we trained random forest models on aggregated data (2010–2020) from the Environmental Agency Open Water Quality Data Archive for 2,343 stations to predict long-term nitrate and orthophosphate concentrations at each river reach in Great Britain (GB). We separated the model training and predictions for different seasons to investigate the potential difference in feature importance. Our model predicted concentrations with an average testing coefficient of determination ( R 2 ) of 0.71 for nitrate and 0.58 for orthophosphate using 5-fold cross-validation. Our model showed slightly better performance for higher Strahler stream orders, highlighting the challenges of making predictions in small streams. Our results revealed that arable and horticultural land use is the strongest and most reliable predictor for nitrate, while floodplain extents and standard percentage runoff are stronger predictors for orthophosphate. Nationally, higher orthophosphate concentrations were observed in urbanised areas. This study shows how combining a river network model with machine learning can easily provide a river network understanding of the spatial distribution of water quality levels.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135109162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.3389/frwa.2023.1128198
Sharad K. Jain, Alok K. Sikka, Mohammad Faiz Alam
Current approaches for utilization of resources in water-energy-food-ecosystem (WEFE) sectors appear to be unsustainable and sub-optimal because of silo-based approaches that ignore interconnectedness across these interdependent sectors. A nexus approach that considers the interactions and interdependence among the sectors helps overcome weaknesses of silo-based approaches to better address synergies and trade-offs. This paper discusses the concept of the WEFE nexus-based approach for achieving water, energy, food, and environment security in India and presents a review of recent relevant literature. The paper critically reviews the key Indian government policies and programmes in the WEFE sector to assess the synergies and trade-offs among them. More than ≈ 40 programmes across WEFE sectors were studied to understand the efforts underway in these sectors to attain the respective policy goals. Although the implementation of the nexus concept will depend upon the enabling government policies and programmes, we find that discussions on these aspects are missing in the literature. Our review shows that the policies of different sectors give inadequate consideration to the impacts of decisions on the other related sectors. Although the various programmes are appreciably contributing to the policy goals and security for respective sectors, there are significant overlaps among the programmes which could positively or negatively impact other sector(s). There is a need to quantify the trade-offs by using an integrated approach including modeling with the WEFE nexus lens. The study also discusses the key challenges and barriers in implementing the nexus concept in India and how to overcome them.
{"title":"Water-energy-food-ecosystem nexus in India—A review of relevant studies, policies, and programmes","authors":"Sharad K. Jain, Alok K. Sikka, Mohammad Faiz Alam","doi":"10.3389/frwa.2023.1128198","DOIUrl":"https://doi.org/10.3389/frwa.2023.1128198","url":null,"abstract":"Current approaches for utilization of resources in water-energy-food-ecosystem (WEFE) sectors appear to be unsustainable and sub-optimal because of silo-based approaches that ignore interconnectedness across these interdependent sectors. A nexus approach that considers the interactions and interdependence among the sectors helps overcome weaknesses of silo-based approaches to better address synergies and trade-offs. This paper discusses the concept of the WEFE nexus-based approach for achieving water, energy, food, and environment security in India and presents a review of recent relevant literature. The paper critically reviews the key Indian government policies and programmes in the WEFE sector to assess the synergies and trade-offs among them. More than ≈ 40 programmes across WEFE sectors were studied to understand the efforts underway in these sectors to attain the respective policy goals. Although the implementation of the nexus concept will depend upon the enabling government policies and programmes, we find that discussions on these aspects are missing in the literature. Our review shows that the policies of different sectors give inadequate consideration to the impacts of decisions on the other related sectors. Although the various programmes are appreciably contributing to the policy goals and security for respective sectors, there are significant overlaps among the programmes which could positively or negatively impact other sector(s). There is a need to quantify the trade-offs by using an integrated approach including modeling with the WEFE nexus lens. The study also discusses the key challenges and barriers in implementing the nexus concept in India and how to overcome them.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.3389/frwa.2023.1227167
Caleb B. Fogel, Katherine B. Lininger
Coarse particulate organic matter (CPOM; organic matter 1–100 mm in diameter, excluding small wood) stored in streams provides an important energy source for aquatic ecosystems, and CPOM transport provides downstream energy subsidies and is a pathway for watershed carbon export. However, we lack understanding of the magnitude of and processes influencing CPOM storage and transport in headwater streams. We assessed how geomorphic complexity and hydrologic regime influence CPOM transport and storage in the Colorado Front Range, USA. We compared CPOM transport during snowmelt in a stream reach with high retentive feature (e.g., wood, cobbles, and other features) frequency to a reach with low retentive feature frequency, assessing how within-a-reach geomorphic context influences CPOM transport. We also compared CPOM transport in reaches with differing valley geometry (two confined reaches versus a wide, multi-thread river bead) to assess the influence of geomorphic variations occurring over larger spatial extents. Additionally, we compared CPOM storage in accumulations in reaches ( n = 14) with flowing water or dry conditions in late summer and investigated how small pieces of organic matter [e.g., woody CPOM and small wood (>1 min length and 0.05–1 min diameter or 0.5–1 min length and >0.1 min diameter)] influence CPOM storage. We found that within-a-reach retentive feature frequency did not influence CPOM transport. However, valley geometry influenced CPOM transport, with a higher CPOM transport rate (median: 1.53 g min −1 ) downstream of a confined stream reach and a lower CPOM transport rate (median: 0.13 g min −1 ) downstream of a low gradient, multi-thread river bead. Additionally, we found that particulate organic carbon (POC) export (0.063 Mg C) in the form of CPOM was substantially lower than dissolved organic carbon (DOC) export (12.3 Mg C) in one of these headwater streams during the 2022 water year. Dry reaches stored a higher volume of CPOM (mean = 29.18 m 3 ha −1 ) compared to reaches with flowing water (15.75 m 3 ha −1 ), and woody CPOM pieces trapped 37% of CPOM accumulations. Our results demonstrate that the influence of geomorphic context on CPOM transport depends on the scale and type of geomorphic complexity, POC may be lower than DOC export in some headwater streams, and small woody organic material is important for trapping CPOM small streams.
粗颗粒有机物(CPOM;河流中储存的1 ~ 100 mm直径的有机物(不包括小木材)为水生生态系统提供了重要的能量来源，CPOM运输为下游提供了能量补贴，是流域碳输出的途径。然而，我们对水源中CPOM储运的影响程度和过程缺乏了解。我们评估了地貌复杂性和水文制度如何影响美国科罗拉多前山脉的cpm运输和储存。我们比较了具有高保留特征(例如，木材，鹅卵石和其他特征)频率的河流河段与具有低保留特征频率的河段在融雪期间的CPOM运输，评估河段内地貌环境如何影响CPOM运输。我们还比较了不同山谷几何形状河段(两个受限河段与一个宽阔的多线程河段)的CPOM输送，以评估在更大空间范围内发生的地貌变化的影响。此外，我们将河段(n = 14)的累积CPOM储量与夏末的流动水或干燥条件进行了比较，并研究了小块有机质[例如木质CPOM和小块木材(长度为1分钟，直径为0.05-1分钟或长度为0.5-1分钟，直径为0.1分钟)]如何影响CPOM储量。我们发现在可及范围内保留特征频率不影响CPOM传输。然而，山谷几何形状影响了CPOM的输送，在受限河段下游，CPOM输送速率较高(中值:1.53 g min - 1)，而在低坡度、多线程河段下游，CPOM输送速率较低(中值:0.13 g min - 1)。此外，我们发现，在2022水年期间，其中一条源流中以CPOM形式输出的颗粒有机碳(POC) (0.063 Mg C)显著低于溶解有机碳(DOC)输出(12.3 Mg C)。与有流水的河段(15.75 m 3 ha - 1)相比，干河段储存了更高的CPOM体积(平均为29.18 m 3 ha - 1)，而木质CPOM片捕获了37%的CPOM积累量。研究结果表明，地貌环境对CPOM运移的影响取决于地貌复杂性的尺度和类型，部分源流的POC可能低于DOC输出，小木本有机物对CPOM小源流的捕获很重要。
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