{'fraction_non_alphanumeric': 0.022113022113022112, 'fraction_numerical': 0.0018427518427518428, 'mean_word_length': 5.621951219512195, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A financial resource allocation model for regional water systems

The public water supply sector is facing significant external pressures for change from decreasing water resource availability, stricter water quality regulations, decreasing federal subsidies, increasing public scrutiny, decreasing financial health, and increasing infrastructure replacement costs. These forces necessitate greater accountability by community water systems (CWS) to their stakeholders. 
 
 
 
This paper presents a method for comparative efficiency analysis to improve the accountability of CWS to their stakeholders while maintaining the level of service. The method is achieved through three objectives, namely: (1) to construct standard efficiency metric parameters based on the techniques of data envelopment analysis; (2) to incorporate these uniform efficiency metric parameters into a transparent decision support system (DSS) based on the standard linear programming resource allocation problem; and (3) to utilize the DSS to determine the efficient allocation of limited budgetary resources among CWS operating as a regional water system (RWS). 
 
 
 
The paper is a significant departure, in three ways, from the current planning and management approach, which treats CWS as independent entities. First, it provides an open and transparent method for planning and management of CWS; second, it provides a uniform and consistent method for evaluating relative efficiencies across the CWS. Third, the DSS facilitates comparative efficiency analysis across the RWS, and guides financial allocation decisions among CWS operating as a RWS.