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Advances in computing, collection, and sharing of Earth Observations (EOs) have significantly improved the potential for integrating EO and water resources models. Inadequate observational data for the systems simulated have been a persistent limitation in developing robust water resources models. Although various EO datasets have been available for decades, they have been under-utilized for water resources modeling. This can be due to sensor and product limitations, including spatial, spectral, and temporal resolutions, and the reluctance of the water resources community to adopt the state-of-art quickly. Motivated by the dual agenda of engaging the water resources community on various aspects of integrating EOs with water resources modeling and understanding the likely factors that limit a deeper integration of EOs in water resources management, we investigated the communities' perception of water resources modeling and EO integration. This paper summarizes the findings of a web-based survey conducted at the annual ASCE-EWRI (American Society of Civil Engineers-Environmental Water Resources Institute) International Water Congress in 2022. The analysis of responses (n = 74) identified limited spatial resolution, atmospheric and cloud interference, and lack of in-situ validation data as the highest perceived barriers to integrating EOs with water resources modeling and management. Perceptions among different groups of participants and even within the groups were different. For example, the perceived barriers often differed between researchers and non-researchers (e.g., policymakers and practitioners). There were differences in perception among the remote-sensing and water resources researchers within the research community. Even among water resources communities, disparities existed between the perceptions of respondents who also identified as knowledgeable about remote sensing and those who didn't. These observations highlighted the need to intentionally develop a convergent group and domain to integrate the disciplines involved and capitalize on the advancements that have improved the EO for water resources management.

The use of Geographic Information Systems (GIS) and remote sensing technologies for the development of water quality management programs and for post-implementation assessments has increased dramatically in the past decade. This increase in adoption has been made more accessible through the interfaces of many popular software tools used in the regulation and assessment of water quality. Customized applications of these tools will increase, as ease of access and affordability of directly monitored and remotely sensed datasets improve over time. Concurrently, there is a need for inclusive participatory engagement with stakeholders to achieve solutions to current watershed management challenges. This paper explores the potential of these GIS and remote sensing datasets, tools, models, and immersive engagement technologies from other domains, for improving public participation and stakeholder engagement throughout the watershed planning process. To do so, an initial review is presented about the use of GIS and remote sensing in watershed management and its role in impairment identification, model development, and planning and implementation. Then, ways in which GIS and remote sensing can be integrated with stakeholder engagement through (1) leveraging GIS and remote sensing datasets, and (2) stakeholder engagement approaches including outreach and education, modeler-led development, and stakeholder-led involvement and feedback, are discussed. Finally, future perspectives on the potential for transforming public participation and stakeholder engagement in the watershed management process through applications of GIS and remote sensing are presented.

Effect of neighbor tree competition on crown shape of Korean pine plantation in Northeast China was studied. A total of 48 trees aged 7-58 years were felled, and all living branches were measured. A novel neighbor competition index that considered the overlap length between subject tree and neighbor tree crowns was created and incorporated into crown shape model. The effects of neighboring competition on crown shape, largest crown radius, and inflection point were analyzed. A dummy variable approach was used to detect crown asymmetry. The crown length index (CLI) of the subject tree was selected as the best neighbor competition index, and the mean square error reduction compared with that of the basic model was 2.0% after incorporating CLI. Crown radius displayed differences in the four cardinal directions and followed the order north > west > south > east. The crown radius in four directions for different ages decreased with increasing CLI and the difference increased with increasing tree age. The competition index, which considers horizontal and vertical competition effects, can significantly improve the performance of crown shape model. Both of inflection point and largest crown radius increased with increasing of CLI; however, the Pearson correlation coefficient was not significant (P > 0.05). Key words: crown radius, crown length index, modified Kozak equation, crown asymmetry, branch analysis L'etude a porte sur l'effet de la concurrence entre arbres voisins sur la forme de la couronne d'une plantation de pins coreens dans le nord-est de la Chine. Au total, 48 arbres ages de 7 a 58 ans ont ete abattus, et toutes les branches vivantes ont ete mesurees. Nous avons cree un nouvel indice de competition entre voisins, qui prend en compte la longueur de chevauchement entre les couronnes de l'arbre sujet et de l'arbre voisin, et nous l'avons integre au modele de forme de couronne. Les effets de la competition des voisins sur la forme de la couronne, le plus grand rayon de la couronne et le point d'inflexion ont ete analyses. L'analyse a utilise une approche par variable muette pour detecter l'asymetrie des couronnes. L'indice de longueur de couronne (ILC) de l'arbre concerne a ete selectionne comme le meilleur indice de competition entre voisins, et la reduction de l'erreur quadratique moyenne par rapport a celle du modele de base etait de 2,0 % apres l'incorporation de l'ILC. Le rayon de la couronne presente des differences dans les quatre directions cardinales et suit l'ordre suivant : nord > ouest > sud > est. Le rayon de la couronne dans les quatre directions pour differents ages a diminue avec l'augmentation de l'ILC et la difference a augmente avec l'age de l'arbre. L'indice de competition, qui prend en compte les effets de la concurrence horizontale et verticale, peut ameliorer considerablement les performances du modele de forme de couronne. Le point d'inflexion et le plus grand rayon de la couronne augmentent avec l'augmentation de l'ILC; cependant, le coefficient de correlation de Pearson n'est pas significatif (P > 0,05). [Traduit par la Redaction] Mots-cles: rayon de la couronne, indice de longueur de couronne, equation de Kozak modifiee, asymetrie de la couronne, analyse des branches, Introduction The crown shape of an individual tree plays an important role in determining tree growth and forest productivity (Valentine et al. 2012) and has a strong functional relationship with [...]

As an important branch characteristic factor, the quantity of branches could influence crown structure, tree growth, and wood quality. Taking Larix kaempferi plantation in Dagujia Forest Farm, Qingyuan County, Liaoning Province as the research object, we developed a mixed effect prediction model of the first-order branches quantity of L. kaempferi including sprouting branches based on the negative binomial distribution model, and a mixed effect prediction model of the first-order branches density of L. kaempferi including sprouting branches based on the negative exponential model. The results showed that the mixed effect model considering sample level as the random effect effectively decreased the heteroscedasticity and autocorrelation. The fitting goodness was better than the traditional model. The quantity of the first-order branches increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches quantity as the random effect parameter was determined as the optimal model, with R.t2 = 0.552 and the RMSE = 7.242. As for the density of the first-order branches, the heteroscedasticity and autocorrelation were also reduced when the random effect was added. The density of the first-order increased with increasing crown ratio. The mixed effect model with the basic model intercept of the first-order branches density model and branch depth as random effects was determined as the optimal model, with Ra2 = 0.792 and the RMSE = 4.447. The model for branch quantity and density of L. kaempferi constructed would lay an important foundation for making scientific forest management plans and improving wood quality [ABSTRACT FROM AUTHOR]

Using the branch data from 90 sample trees, we developed novel models of outer- and inner-crown profiles for the northern, eastern, southern, and western sides of planted Larix kaempferi (Lam.) Carriere trees in northeastern China via the integration of competition indices (CIs) based on nonlinear marginal regression (NMR). We also used nonparametric boundary regression (NBR) to model the crown-profile boundary. The largest crown radius and inflection points of sample trees were calculated using NBR and NMR. We determined that the CIs of the ratio of the diameter of the subject tree to the quadratic mean diameter (CI3) and ratio of the basal area of the subject tree to the mean basal area of the stand ([CI.sub.5]) were the best distance-independent CIs for incorporation into the models of outer- and inner-crown profiles, respectively. The CIs showed a significant effect on the outer-crown profile in all four directions for dominant, intermediate, and suppressed trees but did not show a significant effect on inner-crown profile. The outer-crown radius increased and inner-crown radius decreased with increasing [CI.sub.3] and [CI.sub.5], respectively. The crown profile on the northern side was the largest, which conformed to the regularity in the mean current increment of the sampled branches. Key words: crown profile, competition index, nonlinear marginal regression, nonparametric boundary regression, Larix kaempferi. En utilisant les donnees qui caracterisent les branches de 90 arbres echantillons, nous avons mis au point de nouveaux modeles de profils de cime externe et interne pour les faces nord, est, sud et ouest de Larix kaempferi (Lam.) Carriere plante dans le nord-est de la Chine, en integrant des indices de competition a l'aide de la regression marginale non lineaire (RMNL). Nous avons egalement utilise la regression a limites non parametriques (RLNP) pour modeliser la limite du profil de la cime. Le plus grand rayon de la cime et les points d'inflexion des arbres echantillons ont ete calcules a l'aide de la RLNP et de la RMNL. De plus, nous avons determine que les indices de competition du rapport entre le diametre de l'arbre sujet et le diametre moyen quadratique ([CI.sub.3]), ainsi que le rapport entre la surface terriere de l'arbre sujet et la surface terriere moyenne du peuplement ([CI.sub.5]) etaient respectivement les meilleurs indices de competition independants de la distance a incorporer dans les modeles de profils de cime externe et interne. Les indices de competition avaient un effet significatif sur le profil de cime externe dans les quatre directions pour les arbres dominants, intermediaires et opprimes, mais pas sur le profil de cime interne. Les rayons de cime externe et interne augmentaient et diminuaient respectivement avec une augmentation de [CI.sub.3] et de [CI.sub.5]. Le profil de la cime du cote nord etait le plus grand, ce qui est conforme a la regularite de l'accroissement courant moyen des branches echantillonnees. [Traduit par la Redaction] Mots-cles : profil de cime, indice de competition, regression marginale non lineaire, regression a limites non parametriques, Larix kaempferi., Introduction The crown development of an individual tree is determined by a combination of multiple factors, including intertree competition, growing-site conditions, and intrinsic genetics (Attocchi and Skovsgaard 2015; Sharma et [...]

Forest litter decomposition is an essential component of global carbon and nutrient turnover. Invertebrates play important roles in litter decomposition, but the regional pattern of their effects is poorly understood. We examined 476 case studies across 93 sites and performed a meta‐analysis to estimate regional effects of invertebrates on forest litter decomposition. We then assessed how invertebrate diversity, climate and soil pH drive regional variations in invertebrate‐mediated decomposition. We found that (1) invertebrate contributions to litter decomposition are 1.4 times higher in tropical and subtropical forests than in forests elsewhere, with an overall contribution of 31% to global forest litter decomposition; and (2) termite diversity, together with warm, humid and acidic environments in the tropics and subtropics are positively associated with forest litter decomposition by invertebrates. Our results demonstrate the significant difference in invertebrate effects on mediating forest litter decomposition among regions. We demonstrate, also, the significance of termites in driving litter mass loss in the tropics and subtropics. These results are particularly pertinent in the tropics and subtropics where climate change and human disturbance threaten invertebrate biodiversity and the ecosystem services it provides. [ABSTRACT FROM AUTHOR]

Open water evaporation, which often consumes a large fraction of annual storage (especially in arid and semi‐arid regions), is a controlling variable for modern water resource management. Developing a daily reservoir evaporation data set is necessary for reservoir operations to consider the influence of evaporation in a timely manner. However, over the past few decades, the quantification of reservoir evaporation has primarily relied on monthly Class A pan evaporation observations, which might lead to largely biased estimations because they do not incorporate the effects of heat storage and fetch. In this study, we developed a general Daily Lake Evaporation Model (DLEM) based on Penman's equation combined with daily atmospheric reanalysis data sets, to improve the validity and frequency of reservoir evaporation monitoring. Compared with daily evaporation estimates from eddy covariance systems, the DLEM showed good quality and reliability, with R2 values ranging from 0.50 to 0.73 and RMSE values ranging from 1.13 to 1.97 mm day−1 in four different sites. By applying DLEM to all 188 major reservoirs in Texas, we generated a long‐term data set of (1 January 1981–31 December 2021) daily evaporation rates. The results reveal a clear geographic distribution and strong seasonality of evaporation throughout Texas, where the mean evaporation rate is highest during July, with 6.85 mm day−1. Trend analysis indicates that the annual average evaporation rate has significantly increased since 1981 at a rate of 0.076 mm day−1 decade−1. This study provides sufficient data support for water resource operations and management, and regional water planning. Key Points: A general Daily Lake Evaporation Model (DLEM) is developed on modified‐Penman evaporation and compared with in situ eddy covariance measurementsA first long‐term (40+ years) regional scale daily reservoir evaporation data set is generated for 188 major reservoirs in Texas (US)While shortwave radiation affects the long‐term spatial distribution and trends, high wind speed is likely to cause daily extremes [ABSTRACT FROM AUTHOR]

Evacuation planning and emergency routing systems are crucial in saving lives during disasters. Traditional emergency routing systems, despite their best efforts, often struggle to accurately capture the dynamic nature of flood conditions, road closures, and other real-time changes inherent in urban disaster logistics. This paper introduces the ReinforceRouting model, a novel approach to optimizing evacuation routes using reinforcement learning (RL). The model incorporates a unique RL environment that considers multiple criteria, such as traffic conditions, hazardous situations, and the availability of safe routes. The RL agent in this model learns optimal actions through interaction with the environment, receiving feedback in the form of rewards or penalties. The ReinforceRouting model excels in executing prompt and accurate route planning on large road networks, outperforming traditional RL algorithms and shortest-path-based algorithms. A higher safety score and episode reward of the model are demonstrated when compared to these classical methods. This innovative approach to disaster evacuation planning offers a promising avenue for enhancing the efficiency, safety, and reliability of emergency responses in dynamic urban environments. [ABSTRACT FROM AUTHOR]

This study addresses how site index may affect crown shape by developing a crown shape regression model for the planted L. kaempferi at high altitudes in the subtropical climate of China. A total of 9241 branches from 78 trees, including 39 dominant trees and 39 intermediate trees, were measured in Hubei Province, southern China. The branch characteristics, including branch length, branch angle, and branch chord length of all living branches, were measured by felling trees. The models that showed good performance in crown shape modeling were used and compared in the present study. The goodness of fit statistics and stability of parameter estimation of the modified Kozak equation were better than those of the segmented polynomial equation. A nonlinear mixed-effect crown shape model was developed based on the modified Kozak equation. In addition to the tree level variables of diameter at the breast height (DBH), crown ratio (CR), and tree height-to-DBH ratio, an attempt was made to incorporate the site index into the crown shape model for the planted L. kaempferi. However, the site index was not a significant variable in the crown shape model. The purpose of our study was to lay the foundation for further study of the growth of the trees and the effects of crown morphology on stem growth in the future. [ABSTRACT FROM AUTHOR]